{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('..')\n",
    "from configure.settings import DBSelector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "db = DBSelector()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('roe_pe.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"['Unnamed: 0'] not found in axis\"",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-11-e74991fe962c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Unnamed: 0'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mC:\\anaconda\\lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36mdrop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   4160\u001b[0m                 \u001b[0mweight\u001b[0m  \u001b[1;36m1.0\u001b[0m     \u001b[1;36m0.8\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4161\u001b[0m         \"\"\"\n\u001b[1;32m-> 4162\u001b[1;33m         return super().drop(\n\u001b[0m\u001b[0;32m   4163\u001b[0m             \u001b[0mlabels\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4164\u001b[0m             \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\anaconda\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36mdrop\u001b[1;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[0;32m   3882\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[1;32min\u001b[0m \u001b[0maxes\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3883\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3884\u001b[1;33m                 \u001b[0mobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3885\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3886\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\anaconda\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36m_drop_axis\u001b[1;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[0;32m   3916\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3917\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3918\u001b[1;33m                 \u001b[0mnew_axis\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3919\u001b[0m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3920\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\anaconda\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36mdrop\u001b[1;34m(self, labels, errors)\u001b[0m\n\u001b[0;32m   5276\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mmask\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0many\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5277\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;34m\"ignore\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 5278\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf\"{labels[mask]} not found in axis\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   5279\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   5280\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: \"['Unnamed: 0'] not found in axis\""
     ]
    }
   ],
   "source": [
    "df.drop('Unnamed: 0',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 362 entries, 0 to 361\n",
      "Data columns (total 6 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   Unnamed: 0  362 non-null    int64  \n",
      " 1   bond        362 non-null    int64  \n",
      " 2   name        362 non-null    object \n",
      " 3   pe          362 non-null    float64\n",
      " 4   roe         362 non-null    float64\n",
      " 5   zg_code     362 non-null    int64  \n",
      "dtypes: float64(2), int64(3), object(1)\n",
      "memory usage: 17.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df[['bond','name','pe','roe','zg_code']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bond</th>\n",
       "      <th>name</th>\n",
       "      <th>pe</th>\n",
       "      <th>roe</th>\n",
       "      <th>zg_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>110031</td>\n",
       "      <td>航信转债</td>\n",
       "      <td>13.5730</td>\n",
       "      <td>7.503275</td>\n",
       "      <td>600271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>110033</td>\n",
       "      <td>国贸转债</td>\n",
       "      <td>5.0221</td>\n",
       "      <td>6.168038</td>\n",
       "      <td>600755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>110034</td>\n",
       "      <td>九州转债</td>\n",
       "      <td>9.7541</td>\n",
       "      <td>4.559387</td>\n",
       "      <td>600998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>110038</td>\n",
       "      <td>济川转债</td>\n",
       "      <td>13.6487</td>\n",
       "      <td>19.987800</td>\n",
       "      <td>600566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>110041</td>\n",
       "      <td>蒙电转债</td>\n",
       "      <td>18.4247</td>\n",
       "      <td>4.442312</td>\n",
       "      <td>600863</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     bond  name       pe        roe  zg_code\n",
       "0  110031  航信转债  13.5730   7.503275   600271\n",
       "1  110033  国贸转债   5.0221   6.168038   600755\n",
       "2  110034  九州转债   9.7541   4.559387   600998\n",
       "3  110038  济川转债  13.6487  19.987800   600566\n",
       "4  110041  蒙电转债  18.4247   4.442312   600863"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "engine = db.get_engine('db_stock','qq')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.read_sql('')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4166666666666667"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "5/12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3.4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "path=r'D:\\Temp\\100buy_130sell.txt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(path,'r',encoding='utf8') as fp:\n",
    "    content = fp.readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "676"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2018-01-02 00:00:00 [INFO] 20180102 买入128013.XSHE, 洪涛转债, 价格92.74, 溢价率93.4015\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入127003.XSHE, 海印转债, 价格93.1, 溢价率60.7812\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入127004.XSHE, 模塑转债, 价格93.5, 溢价率30.541\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入128023.XSHE, 亚太转债, 价格95.24, 溢价率10.6012\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入128018.XSHE, 时达转债, 价格95.4, 溢价率11.8482\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入128019.XSHE, 久立转2, 价格95.5, 溢价率10.8647\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入128012.XSHE, 辉丰转债, 价格95.602, 溢价率32.372\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入128015.XSHE, 久其转债, 价格96.2, 溢价率19.5549\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入113502.XSHG, 嘉澳转债, 价格96.29, 溢价率24.5171\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102 买入113012.XSHG, 骆驼转债, 价格96.46, 溢价率21.264\\n',\n",
       " '2018-01-02 00:00:00 [INFO] 20180102: 最高市值 1000000 , 当前市值 1000000收益率 ： 0% , 最大回撤 0.0%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-01-09 00:00:00 [INFO] 20180109: 最高市值 1019485.8 , 当前市值 1019485.8收益率 ： 1.94858% , 最大回撤 0.0%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-01-16 00:00:00 [INFO] 20180116: 最高市值 1019485.8 , 当前市值 1006855.67收益率 ： 0.685567% , 最大回撤 1.24%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-01-23 00:00:00 [INFO] 20180123: 最高市值 1019485.8 , 当前市值 1016548.52收益率 ： 1.654852% , 最大回撤 1.24%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-01-30 00:00:00 [INFO] 20180130: 最高市值 1023342.65 , 当前市值 1023342.65收益率 ： 2.334265% , 最大回撤 1.24%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-02-06 00:00:00 [INFO] 20180206: 最高市值 1023342.65 , 当前市值 1004610.09收益率 ： 0.461009% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-02-13 00:00:00 [INFO] 20180213: 最高市值 1023342.65 , 当前市值 1005110.85收益率 ： 0.511085% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-02-27 00:00:00 [INFO] 20180227: 最高市值 1023342.65 , 当前市值 1014736.64收益率 ： 1.473664% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-03-06 00:00:00 [INFO] 20180306: 最高市值 1023342.65 , 当前市值 1018164.08收益率 ： 1.816408% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-03-13 00:00:00 [INFO] 20180313: 最高市值 1034313.13 , 当前市值 1034313.13收益率 ： 3.431313% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-03-20 00:00:00 [INFO] 20180320: 最高市值 1034313.13 , 当前市值 1029096.43收益率 ： 2.909643% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-03-27 00:00:00 [INFO] 20180327: 最高市值 1034313.13 , 当前市值 1024827.5收益率 ： 2.48275% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-04-03 00:00:00 [INFO] 20180403: 最高市值 1034313.13 , 当前市值 1029394.53收益率 ： 2.939453% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-04-12 00:00:00 [INFO] 20180412: 最高市值 1034313.13 , 当前市值 1030253.87收益率 ： 3.025387% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-04-19 00:00:00 [INFO] 20180419: 最高市值 1034313.13 , 当前市值 1028159.44收益率 ： 2.815944% , 最大回撤 1.83%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-04-26 00:00:00 [INFO] 20180426: 最高市值 1034313.13 , 当前市值 1008386.97收益率 ： 0.838697% , 最大回撤 2.51%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-05-07 00:00:00 [INFO] 20180507: 最高市值 1034313.13 , 当前市值 1013075.85收益率 ： 1.307585% , 最大回撤 2.51%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-05-14 00:00:00 [INFO] 20180514: 最高市值 1034313.13 , 当前市值 1001511.62收益率 ： 0.151162% , 最大回撤 3.17%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-05-21 00:00:00 [INFO] 20180521: 最高市值 1034313.13 , 当前市值 1003478.14收益率 ： 0.347814% , 最大回撤 3.17%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-05-28 00:00:00 [INFO] 20180528: 最高市值 1034313.13 , 当前市值 982021.71收益率 ： -1.797829% , 最大回撤 5.06%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-06-04 00:00:00 [INFO] 20180604: 最高市值 1034313.13 , 当前市值 953676.72收益率 ： -4.632328% , 最大回撤 7.8%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-06-11 00:00:00 [INFO] 20180611: 最高市值 1034313.13 , 当前市值 959140.2收益率 ： -4.08598% , 最大回撤 7.8%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-06-19 00:00:00 [INFO] 20180619: 最高市值 1034313.13 , 当前市值 912373.4收益率 ： -8.76266% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-06-26 00:00:00 [INFO] 20180626: 最高市值 1034313.13 , 当前市值 926585.01收益率 ： -7.341499% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-07-03 00:00:00 [INFO] 20180703: 最高市值 1034313.13 , 当前市值 925741.66收益率 ： -7.425834% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-07-10 00:00:00 [INFO] 20180710: 最高市值 1034313.13 , 当前市值 926568.12收益率 ： -7.343188% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-07-17 00:00:00 [INFO] 20180717: 最高市值 1034313.13 , 当前市值 935145.46收益率 ： -6.485454% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-07-24 00:00:00 [INFO] 20180724: 最高市值 1034313.13 , 当前市值 961669.37收益率 ： -3.833063% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-07-31 00:00:00 [INFO] 20180731: 最高市值 1034313.13 , 当前市值 949295.29收益率 ： -5.070471% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-08-07 00:00:00 [INFO] 20180807: 最高市值 1034313.13 , 当前市值 937448.8收益率 ： -6.25512% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-08-14 00:00:00 [INFO] 20180814: 最高市值 1034313.13 , 当前市值 935961.28收益率 ： -6.403872% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-08-21 00:00:00 [INFO] 20180821: 最高市值 1034313.13 , 当前市值 931240.41收益率 ： -6.875959% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-08-28 00:00:00 [INFO] 20180828: 最高市值 1034313.13 , 当前市值 934905.2收益率 ： -6.50948% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-09-04 00:00:00 [INFO] 20180904: 最高市值 1034313.13 , 当前市值 937971.97收益率 ： -6.202803% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-09-11 00:00:00 [INFO] 20180911: 最高市值 1034313.13 , 当前市值 935027.05收益率 ： -6.497295% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-09-18 00:00:00 [INFO] 20180918: 最高市值 1034313.13 , 当前市值 935762.18收益率 ： -6.423782% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-09-26 00:00:00 [INFO] 20180926: 最高市值 1034313.13 , 当前市值 937160.64收益率 ： -6.283936% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-10-10 00:00:00 [INFO] 20181010: 最高市值 1034313.13 , 当前市值 930320.99收益率 ： -6.967901% , 最大回撤 11.79%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-10-17 00:00:00 [INFO] 20181017: 最高市值 1034313.13 , 当前市值 911561.35收益率 ： -8.843865% , 最大回撤 11.87%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-10-24 00:00:00 [INFO] 20181024: 最高市值 1034313.13 , 当前市值 910911.25收益率 ： -8.908875% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-10-31 00:00:00 [INFO] 20181031: 最高市值 1034313.13 , 当前市值 924176.77收益率 ： -7.582323% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-11-07 00:00:00 [INFO] 20181107: 最高市值 1034313.13 , 当前市值 938910.86收益率 ： -6.108914% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-11-14 00:00:00 [INFO] 20181114: 最高市值 1034313.13 , 当前市值 947895.92收益率 ： -5.210408% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-11-21 00:00:00 [INFO] 20181121: 最高市值 1034313.13 , 当前市值 952941.92收益率 ： -4.705808% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-11-28 00:00:00 [INFO] 20181128: 最高市值 1034313.13 , 当前市值 953171.0收益率 ： -4.6829% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-12-05 00:00:00 [INFO] 20181205: 最高市值 1034313.13 , 当前市值 959722.28收益率 ： -4.027772% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-12-12 00:00:00 [INFO] 20181212: 最高市值 1034313.13 , 当前市值 959904.76收益率 ： -4.009524% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-12-19 00:00:00 [INFO] 20181219: 最高市值 1034313.13 , 当前市值 949243.34收益率 ： -5.075666% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2018-12-26 00:00:00 [INFO] 20181226: 最高市值 1034313.13 , 当前市值 939107.11收益率 ： -6.089289% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-01-04 00:00:00 [INFO] 20190104: 最高市值 1034313.13 , 当前市值 949904.48收益率 ： -5.009552% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-01-11 00:00:00 [INFO] 20190111: 最高市值 1034313.13 , 当前市值 972877.59收益率 ： -2.712241% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-01-18 00:00:00 [INFO] 20190118: 最高市值 1034313.13 , 当前市值 972218.32收益率 ： -2.778168% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-01-25 00:00:00 [INFO] 20190125: 最高市值 1034313.13 , 当前市值 972496.46收益率 ： -2.750354% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-02-01 00:00:00 [INFO] 20190201: 最高市值 1034313.13 , 当前市值 974285.03收益率 ： -2.571497% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-02-15 00:00:00 [INFO] 20190215: 最高市值 1034313.13 , 当前市值 996362.21收益率 ： -0.363779% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-02-22 00:00:00 [INFO] 20190222: 最高市值 1034313.13 , 当前市值 1009926.39收益率 ： 0.992639% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-03-01 00:00:00 [INFO] 20190301: 最高市值 1034313.13 , 当前市值 1024587.71收益率 ： 2.458771% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-03-08 00:00:00 [INFO] 20190308: 最高市值 1066158.37 , 当前市值 1066158.37收益率 ： 6.615837% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-03-15 00:00:00 [INFO] 20190315: 最高市值 1074351.72 , 当前市值 1074351.72收益率 ： 7.435172% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-03-22 00:00:00 [INFO] 20190322: 最高市值 1110313.2 , 当前市值 1110313.2收益率 ： 11.03132% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-03-29 00:00:00 [INFO] 20190329: 最高市值 1110313.2 , 当前市值 1100386.27收益率 ： 10.038627% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-04-08 00:00:00 [INFO] 20190408: 最高市值 1142570.65 , 当前市值 1142570.65收益率 ： 14.257065% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-04-15 00:00:00 [INFO] 20190415: 最高市值 1142570.65 , 当前市值 1103360.15收益率 ： 10.336015% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-04-22 00:00:00 [INFO] 20190422: 最高市值 1142570.65 , 当前市值 1096712.0收益率 ： 9.6712% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-04-29 00:00:00 [INFO] 20190429: 最高市值 1142570.65 , 当前市值 1044416.13收益率 ： 4.441613% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-05-09 00:00:00 [INFO] 20190509: 最高市值 1142570.65 , 当前市值 1032354.7收益率 ： 3.23547% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-05-16 00:00:00 [INFO] 20190516: 最高市值 1142570.65 , 当前市值 1053131.4收益率 ： 5.31314% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-05-23 00:00:00 [INFO] 20190523: 最高市值 1142570.65 , 当前市值 1035776.63收益率 ： 3.577663% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-05-30 00:00:00 [INFO] 20190530: 最高市值 1142570.65 , 当前市值 1031358.79收益率 ： 3.135879% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-06-06 00:00:00 [INFO] 20190606: 最高市值 1142570.65 , 当前市值 1010570.67收益率 ： 1.057067% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-06-14 00:00:00 [INFO] 20190614: 最高市值 1142570.65 , 当前市值 1016367.93收益率 ： 1.636793% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-06-21 00:00:00 [INFO] 20190621: 最高市值 1142570.65 , 当前市值 1035052.16收益率 ： 3.505216% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-06-28 00:00:00 [INFO] 20190628: 最高市值 1142570.65 , 当前市值 1025246.55收益率 ： 2.524655% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-07-05 00:00:00 [INFO] 20190705: 最高市值 1142570.65 , 当前市值 1033585.21收益率 ： 3.358521% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-07-12 00:00:00 [INFO] 20190712: 最高市值 1142570.65 , 当前市值 1025945.07收益率 ： 2.594507% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-07-19 00:00:00 [INFO] 20190719: 最高市值 1142570.65 , 当前市值 1028036.12收益率 ： 2.803612% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-07-26 00:00:00 [INFO] 20190726: 最高市值 1142570.65 , 当前市值 1029270.62收益率 ： 2.927062% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-08-02 00:00:00 [INFO] 20190802: 最高市值 1142570.65 , 当前市值 1023517.01收益率 ： 2.351701% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-08-09 00:00:00 [INFO] 20190809: 最高市值 1142570.65 , 当前市值 1020980.32收益率 ： 2.098032% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-08-16 00:00:00 [INFO] 20190816: 最高市值 1142570.65 , 当前市值 1023731.84收益率 ： 2.373184% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-08-23 00:00:00 [INFO] 20190823: 最高市值 1142570.65 , 当前市值 1030555.62收益率 ： 3.055562% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-08-30 00:00:00 [INFO] 20190830: 最高市值 1142570.65 , 当前市值 1036604.5收益率 ： 3.66045% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-09-06 00:00:00 [INFO] 20190906: 最高市值 1142570.65 , 当前市值 1047378.92收益率 ： 4.737892% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-09-16 00:00:00 [INFO] 20190916: 最高市值 1142570.65 , 当前市值 1060725.38收益率 ： 6.072538% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-09-23 00:00:00 [INFO] 20190923: 最高市值 1142570.65 , 当前市值 1055619.11收益率 ： 5.561911% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-09-30 00:00:00 [INFO] 20190930: 最高市值 1142570.65 , 当前市值 1055244.47收益率 ： 5.524447% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-10-14 00:00:00 [INFO] 20191014: 最高市值 1142570.65 , 当前市值 1065143.45收益率 ： 6.514345% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-10-21 00:00:00 [INFO] 20191021: 最高市值 1142570.65 , 当前市值 1053393.98收益率 ： 5.339398% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-10-28 00:00:00 [INFO] 20191028: 最高市值 1142570.65 , 当前市值 1060076.3收益率 ： 6.00763% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-11-04 00:00:00 [INFO] 20191104: 最高市值 1142570.65 , 当前市值 1056978.01收益率 ： 5.697801% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-11-11 00:00:00 [INFO] 20191111: 最高市值 1142570.65 , 当前市值 1057162.32收益率 ： 5.716232% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-11-18 00:00:00 [INFO] 20191118: 最高市值 1142570.65 , 当前市值 1057912.73收益率 ： 5.791273% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-11-25 00:00:00 [INFO] 20191125: 最高市值 1142570.65 , 当前市值 1054589.9收益率 ： 5.45899% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-12-02 00:00:00 [INFO] 20191202: 最高市值 1142570.65 , 当前市值 1049703.13收益率 ： 4.970313% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-12-09 00:00:00 [INFO] 20191209: 最高市值 1142570.65 , 当前市值 1051727.53收益率 ： 5.172753% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-12-16 00:00:00 [INFO] 20191216: 最高市值 1142570.65 , 当前市值 1059400.45收益率 ： 5.940045% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-12-23 00:00:00 [INFO] 20191223: 最高市值 1142570.65 , 当前市值 1058768.8收益率 ： 5.87688% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2019-12-30 00:00:00 [INFO] 20191230: 最高市值 1142570.65 , 当前市值 1071569.01收益率 ： 7.156901% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-01-07 00:00:00 [INFO] 20200107: 最高市值 1142570.65 , 当前市值 1093977.27收益率 ： 9.397727% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-01-14 00:00:00 [INFO] 20200114: 最高市值 1142570.65 , 当前市值 1106116.71收益率 ： 10.611671% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-01-21 00:00:00 [INFO] 20200121 卖出127004.XSHE,模塑转债,价格：133.12\\n',\n",
       " '2020-01-21 00:00:00 [INFO] 20200121 买入128062.XSHE, 亚药转债, 价格90.421, 溢价率109.9058\\n',\n",
       " '2020-01-21 00:00:00 [INFO] 20200121: 最高市值 1142570.65 , 当前市值 1135617.53收益率 ： 13.561753% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-02-05 00:00:00 [INFO] 20200205: 最高市值 1142570.65 , 当前市值 1118438.94收益率 ： 11.843894% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-02-12 00:00:00 [INFO] 20200212: 最高市值 1142845.52 , 当前市值 1142845.52收益率 ： 14.284552% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-02-19 00:00:00 [INFO] 20200219: 最高市值 1164168.45 , 当前市值 1164168.45收益率 ： 16.416845% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-02-26 00:00:00 [INFO] 20200226: 最高市值 1172744.24 , 当前市值 1172744.24收益率 ： 17.274424% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-03-04 00:00:00 [INFO] 20200304: 最高市值 1172744.24 , 当前市值 1170302.44收益率 ： 17.030244% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-03-11 00:00:00 [INFO] 20200311: 最高市值 1172744.24 , 当前市值 1168426.84收益率 ： 16.842684% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-03-18 00:00:00 [INFO] 20200318: 最高市值 1172744.24 , 当前市值 1155576.38收益率 ： 15.557638% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-03-25 00:00:00 [INFO] 20200325: 最高市值 1175343.21 , 当前市值 1175343.21收益率 ： 17.534321% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-04-01 00:00:00 [INFO] 20200401: 最高市值 1175343.21 , 当前市值 1158367.54收益率 ： 15.836754% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-04-09 00:00:00 [INFO] 20200409: 最高市值 1175343.21 , 当前市值 1152448.53收益率 ： 15.244853% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-04-16 00:00:00 [INFO] 20200416: 最高市值 1175343.21 , 当前市值 1149661.6收益率 ： 14.96616% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-04-23 00:00:00 [INFO] 20200423: 最高市值 1175343.21 , 当前市值 1154226.99收益率 ： 15.422699% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-04-30 00:00:00 [INFO] 20200430: 最高市值 1175343.21 , 当前市值 1149661.97收益率 ： 14.966197% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-05-12 00:00:00 [INFO] 20200512: 最高市值 1175343.21 , 当前市值 1144152.85收益率 ： 14.415285% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-05-19 00:00:00 [INFO] 20200519: 最高市值 1175343.21 , 当前市值 1108768.65收益率 ： 10.876865% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-05-26 00:00:00 [INFO] 20200526: 最高市值 1175343.21 , 当前市值 1097396.08收益率 ： 9.739608% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-06-02 00:00:00 [INFO] 20200602: 最高市值 1175343.21 , 当前市值 1113865.56收益率 ： 11.386556% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-06-09 00:00:00 [INFO] 20200609: 最高市值 1175343.21 , 当前市值 1109978.3收益率 ： 10.99783% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-06-16 00:00:00 [INFO] 20200616: 最高市值 1175343.21 , 当前市值 1109230.7收益率 ： 10.92307% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-06-23 00:00:00 [INFO] 20200623: 最高市值 1175343.21 , 当前市值 1105081.11收益率 ： 10.508111% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-07-02 00:00:00 [INFO] 20200702: 最高市值 1175343.21 , 当前市值 1101981.57收益率 ： 10.198157% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-07-09 00:00:00 [INFO] 20200709: 最高市值 1175343.21 , 当前市值 1155403.53收益率 ： 15.540353% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-07-16 00:00:00 [INFO] 20200716: 最高市值 1175343.21 , 当前市值 1120031.12收益率 ： 12.003112% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-07-23 00:00:00 [INFO] 20200723: 最高市值 1175343.21 , 当前市值 1150020.95收益率 ： 15.002095% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-07-30 00:00:00 [INFO] 20200730: 最高市值 1175343.21 , 当前市值 1158344.49收益率 ： 15.834449% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-08-06 00:00:00 [INFO] 20200806: 最高市值 1175343.21 , 当前市值 1165282.57收益率 ： 16.528257% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-08-13 00:00:00 [INFO] 20200813: 最高市值 1175343.21 , 当前市值 1157341.18收益率 ： 15.734118% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-08-20 00:00:00 [INFO] 20200820: 最高市值 1175343.21 , 当前市值 1155369.4收益率 ： 15.53694% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-08-27 00:00:00 [INFO] 20200827: 最高市值 1175343.21 , 当前市值 1153798.43收益率 ： 15.379843% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-09-03 00:00:00 [INFO] 20200903 卖出128019.XSHE,久立转2,价格：130.22\\n',\n",
       " '2020-09-03 00:00:00 [INFO] 20200903 买入113527.XSHG, 维格转债, 价格94.04, 溢价率33.2797\\n',\n",
       " '2020-09-03 00:00:00 [INFO] 20200903: 最高市值 1175343.21 , 当前市值 1167333.11收益率 ： 16.733311% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-09-10 00:00:00 [INFO] 20200910: 最高市值 1175343.21 , 当前市值 1151287.88收益率 ： 15.128788% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-09-17 00:00:00 [INFO] 20200917: 最高市值 1175343.21 , 当前市值 1150909.54收益率 ： 15.090954% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-09-24 00:00:00 [INFO] 20200924: 最高市值 1175343.21 , 当前市值 1133619.52收益率 ： 13.361952% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-10-09 00:00:00 [INFO] 20201009: 最高市值 1175343.21 , 当前市值 1130395.17收益率 ： 13.039517% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-10-16 00:00:00 [INFO] 20201016: 最高市值 1175343.21 , 当前市值 1135831.21收益率 ： 13.583121% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-10-23 00:00:00 [INFO] 20201023: 最高市值 1175343.21 , 当前市值 1156312.48收益率 ： 15.631248% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-10-30 00:00:00 [INFO] 20201030: 最高市值 1175343.21 , 当前市值 1126505.89收益率 ： 12.650589% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-11-06 00:00:00 [INFO] 20201106: 最高市值 1175343.21 , 当前市值 1132095.43收益率 ： 13.209543% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-11-13 00:00:00 [INFO] 20201113: 最高市值 1175343.21 , 当前市值 1131853.84收益率 ： 13.185384% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-11-20 00:00:00 [INFO] 20201120: 最高市值 1175343.21 , 当前市值 1121621.53收益率 ： 12.162153% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-11-27 00:00:00 [INFO] 20201127: 最高市值 1175343.21 , 当前市值 1128931.7收益率 ： 12.89317% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-12-04 00:00:00 [INFO] 20201204: 最高市值 1175343.21 , 当前市值 1125559.12收益率 ： 12.555912% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-12-11 00:00:00 [INFO] 20201211: 最高市值 1175343.21 , 当前市值 1109316.81收益率 ： 10.931681% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-12-18 00:00:00 [INFO] 20201218: 最高市值 1175343.21 , 当前市值 1091760.07收益率 ： 9.176007% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2020-12-25 00:00:00 [INFO] 20201225: 最高市值 1175343.21 , 当前市值 1069978.12收益率 ： 6.997812% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-01-04 00:00:00 [INFO] 20210104: 最高市值 1175343.21 , 当前市值 1084869.86收益率 ： 8.486986% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-01-11 00:00:00 [INFO] 20210111: 最高市值 1175343.21 , 当前市值 1072493.4收益率 ： 7.24934% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-01-18 00:00:00 [INFO] 20210118: 最高市值 1175343.21 , 当前市值 1081348.52收益率 ： 8.134852% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-01-25 00:00:00 [INFO] 20210125: 最高市值 1175343.21 , 当前市值 1071431.59收益率 ： 7.143159% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-02-01 00:00:00 [INFO] 20210201: 最高市值 1175343.21 , 当前市值 1051394.98收益率 ： 5.139498% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-02-08 00:00:00 [INFO] 20210208: 最高市值 1175343.21 , 当前市值 1049346.61收益率 ： 4.934661% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-02-22 00:00:00 [INFO] 20210222: 最高市值 1175343.21 , 当前市值 1080455.78收益率 ： 8.045578% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-03-01 00:00:00 [INFO] 20210301: 最高市值 1175343.21 , 当前市值 1088693.53收益率 ： 8.869353% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-03-08 00:00:00 [INFO] 20210308: 最高市值 1175343.21 , 当前市值 1090203.88收益率 ： 9.020388% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-03-15 00:00:00 [INFO] 20210315 卖出113502.XSHG,嘉澳转债,价格：133.72\\n',\n",
       " '2021-03-15 00:00:00 [INFO] 20210315 买入128100.XSHE, 搜特转债, 价格80.78, 溢价率32.3514\\n',\n",
       " '2021-03-15 00:00:00 [INFO] 20210315: 最高市值 1175343.21 , 当前市值 1130165.04收益率 ： 13.016504% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-03-22 00:00:00 [INFO] 20210322: 最高市值 1175343.21 , 当前市值 1157240.58收益率 ： 15.724058% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-03-29 00:00:00 [INFO] 20210329: 最高市值 1175343.21 , 当前市值 1153544.89收益率 ： 15.354489% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-04-06 00:00:00 [INFO] 20210406: 最高市值 1175343.21 , 当前市值 1152595.41收益率 ： 15.259541% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-04-13 00:00:00 [INFO] 20210413: 最高市值 1175343.21 , 当前市值 1167145.27收益率 ： 16.714527% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-04-20 00:00:00 [INFO] 20210420: 最高市值 1199423.08 , 当前市值 1199423.08收益率 ： 19.942308% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-04-27 00:00:00 [INFO] 20210427 卖出113527.XSHG,维格转债,价格：152.49\\n',\n",
       " '2021-04-27 00:00:00 [INFO] 20210427 买入110072.XSHG, 广汇转债, 价格88.17, 溢价率21.6866\\n',\n",
       " '2021-04-27 00:00:00 [INFO] 20210427: 最高市值 1275089.27 , 当前市值 1275089.27收益率 ： 27.508927% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-05-07 00:00:00 [INFO] 20210507: 最高市值 1284866.8 , 当前市值 1284866.8收益率 ： 28.48668% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-05-14 00:00:00 [INFO] 20210514: 最高市值 1301801.35 , 当前市值 1301801.35收益率 ： 30.180135% , 最大回撤 11.93%\\n',\n",
       " '====================\\n',\n",
       " '\\n',\n",
       " '\\n',\n",
       " '2021-05-21 00:00:00 [INFO] 20210521: 最高市值 1305663.34 , 当前市值 1305663.34收益率 ： 30.566334% , 最大回撤 11.93%\\n',\n",
       " '====================']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "result=[]\n",
    "for line in content:\n",
    "    line=line.strip()\n",
    "    if line:\n",
    "#         print(line)\n",
    "        m=re.search('(.*?) 00:00:00 .*?收益率 ： (.*?)% ',line)\n",
    "        if m:\n",
    "            date=m.group(1)\n",
    "            profit=m.group(2)\n",
    "            result.append({'date':date,'profit':profit})\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'date': '2018-01-02', 'profit': '0'},\n",
       " {'date': '2018-01-09', 'profit': '1.94858'},\n",
       " {'date': '2018-01-16', 'profit': '0.685567'},\n",
       " {'date': '2018-01-23', 'profit': '1.654852'},\n",
       " {'date': '2018-01-30', 'profit': '2.334265'},\n",
       " {'date': '2018-02-06', 'profit': '0.461009'},\n",
       " {'date': '2018-02-13', 'profit': '0.511085'},\n",
       " {'date': '2018-02-27', 'profit': '1.473664'},\n",
       " {'date': '2018-03-06', 'profit': '1.816408'},\n",
       " {'date': '2018-03-13', 'profit': '3.431313'},\n",
       " {'date': '2018-03-20', 'profit': '2.909643'},\n",
       " {'date': '2018-03-27', 'profit': '2.48275'},\n",
       " {'date': '2018-04-03', 'profit': '2.939453'},\n",
       " {'date': '2018-04-12', 'profit': '3.025387'},\n",
       " {'date': '2018-04-19', 'profit': '2.815944'},\n",
       " {'date': '2018-04-26', 'profit': '0.838697'},\n",
       " {'date': '2018-05-07', 'profit': '1.307585'},\n",
       " {'date': '2018-05-14', 'profit': '0.151162'},\n",
       " {'date': '2018-05-21', 'profit': '0.347814'},\n",
       " {'date': '2018-05-28', 'profit': '-1.797829'},\n",
       " {'date': '2018-06-04', 'profit': '-4.632328'},\n",
       " {'date': '2018-06-11', 'profit': '-4.08598'},\n",
       " {'date': '2018-06-19', 'profit': '-8.76266'},\n",
       " {'date': '2018-06-26', 'profit': '-7.341499'},\n",
       " {'date': '2018-07-03', 'profit': '-7.425834'},\n",
       " {'date': '2018-07-10', 'profit': '-7.343188'},\n",
       " {'date': '2018-07-17', 'profit': '-6.485454'},\n",
       " {'date': '2018-07-24', 'profit': '-3.833063'},\n",
       " {'date': '2018-07-31', 'profit': '-5.070471'},\n",
       " {'date': '2018-08-07', 'profit': '-6.25512'},\n",
       " {'date': '2018-08-14', 'profit': '-6.403872'},\n",
       " {'date': '2018-08-21', 'profit': '-6.875959'},\n",
       " {'date': '2018-08-28', 'profit': '-6.50948'},\n",
       " {'date': '2018-09-04', 'profit': '-6.202803'},\n",
       " {'date': '2018-09-11', 'profit': '-6.497295'},\n",
       " {'date': '2018-09-18', 'profit': '-6.423782'},\n",
       " {'date': '2018-09-26', 'profit': '-6.283936'},\n",
       " {'date': '2018-10-10', 'profit': '-6.967901'},\n",
       " {'date': '2018-10-17', 'profit': '-8.843865'},\n",
       " {'date': '2018-10-24', 'profit': '-8.908875'},\n",
       " {'date': '2018-10-31', 'profit': '-7.582323'},\n",
       " {'date': '2018-11-07', 'profit': '-6.108914'},\n",
       " {'date': '2018-11-14', 'profit': '-5.210408'},\n",
       " {'date': '2018-11-21', 'profit': '-4.705808'},\n",
       " {'date': '2018-11-28', 'profit': '-4.6829'},\n",
       " {'date': '2018-12-05', 'profit': '-4.027772'},\n",
       " {'date': '2018-12-12', 'profit': '-4.009524'},\n",
       " {'date': '2018-12-19', 'profit': '-5.075666'},\n",
       " {'date': '2018-12-26', 'profit': '-6.089289'},\n",
       " {'date': '2019-01-04', 'profit': '-5.009552'},\n",
       " {'date': '2019-01-11', 'profit': '-2.712241'},\n",
       " {'date': '2019-01-18', 'profit': '-2.778168'},\n",
       " {'date': '2019-01-25', 'profit': '-2.750354'},\n",
       " {'date': '2019-02-01', 'profit': '-2.571497'},\n",
       " {'date': '2019-02-15', 'profit': '-0.363779'},\n",
       " {'date': '2019-02-22', 'profit': '0.992639'},\n",
       " {'date': '2019-03-01', 'profit': '2.458771'},\n",
       " {'date': '2019-03-08', 'profit': '6.615837'},\n",
       " {'date': '2019-03-15', 'profit': '7.435172'},\n",
       " {'date': '2019-03-22', 'profit': '11.03132'},\n",
       " {'date': '2019-03-29', 'profit': '10.038627'},\n",
       " {'date': '2019-04-08', 'profit': '14.257065'},\n",
       " {'date': '2019-04-15', 'profit': '10.336015'},\n",
       " {'date': '2019-04-22', 'profit': '9.6712'},\n",
       " {'date': '2019-04-29', 'profit': '4.441613'},\n",
       " {'date': '2019-05-09', 'profit': '3.23547'},\n",
       " {'date': '2019-05-16', 'profit': '5.31314'},\n",
       " {'date': '2019-05-23', 'profit': '3.577663'},\n",
       " {'date': '2019-05-30', 'profit': '3.135879'},\n",
       " {'date': '2019-06-06', 'profit': '1.057067'},\n",
       " {'date': '2019-06-14', 'profit': '1.636793'},\n",
       " {'date': '2019-06-21', 'profit': '3.505216'},\n",
       " {'date': '2019-06-28', 'profit': '2.524655'},\n",
       " {'date': '2019-07-05', 'profit': '3.358521'},\n",
       " {'date': '2019-07-12', 'profit': '2.594507'},\n",
       " {'date': '2019-07-19', 'profit': '2.803612'},\n",
       " {'date': '2019-07-26', 'profit': '2.927062'},\n",
       " {'date': '2019-08-02', 'profit': '2.351701'},\n",
       " {'date': '2019-08-09', 'profit': '2.098032'},\n",
       " {'date': '2019-08-16', 'profit': '2.373184'},\n",
       " {'date': '2019-08-23', 'profit': '3.055562'},\n",
       " {'date': '2019-08-30', 'profit': '3.66045'},\n",
       " {'date': '2019-09-06', 'profit': '4.737892'},\n",
       " {'date': '2019-09-16', 'profit': '6.072538'},\n",
       " {'date': '2019-09-23', 'profit': '5.561911'},\n",
       " {'date': '2019-09-30', 'profit': '5.524447'},\n",
       " {'date': '2019-10-14', 'profit': '6.514345'},\n",
       " {'date': '2019-10-21', 'profit': '5.339398'},\n",
       " {'date': '2019-10-28', 'profit': '6.00763'},\n",
       " {'date': '2019-11-04', 'profit': '5.697801'},\n",
       " {'date': '2019-11-11', 'profit': '5.716232'},\n",
       " {'date': '2019-11-18', 'profit': '5.791273'},\n",
       " {'date': '2019-11-25', 'profit': '5.45899'},\n",
       " {'date': '2019-12-02', 'profit': '4.970313'},\n",
       " {'date': '2019-12-09', 'profit': '5.172753'},\n",
       " {'date': '2019-12-16', 'profit': '5.940045'},\n",
       " {'date': '2019-12-23', 'profit': '5.87688'},\n",
       " {'date': '2019-12-30', 'profit': '7.156901'},\n",
       " {'date': '2020-01-07', 'profit': '9.397727'},\n",
       " {'date': '2020-01-14', 'profit': '10.611671'},\n",
       " {'date': '2020-01-21', 'profit': '13.561753'},\n",
       " {'date': '2020-02-05', 'profit': '11.843894'},\n",
       " {'date': '2020-02-12', 'profit': '14.284552'},\n",
       " {'date': '2020-02-19', 'profit': '16.416845'},\n",
       " {'date': '2020-02-26', 'profit': '17.274424'},\n",
       " {'date': '2020-03-04', 'profit': '17.030244'},\n",
       " {'date': '2020-03-11', 'profit': '16.842684'},\n",
       " {'date': '2020-03-18', 'profit': '15.557638'},\n",
       " {'date': '2020-03-25', 'profit': '17.534321'},\n",
       " {'date': '2020-04-01', 'profit': '15.836754'},\n",
       " {'date': '2020-04-09', 'profit': '15.244853'},\n",
       " {'date': '2020-04-16', 'profit': '14.96616'},\n",
       " {'date': '2020-04-23', 'profit': '15.422699'},\n",
       " {'date': '2020-04-30', 'profit': '14.966197'},\n",
       " {'date': '2020-05-12', 'profit': '14.415285'},\n",
       " {'date': '2020-05-19', 'profit': '10.876865'},\n",
       " {'date': '2020-05-26', 'profit': '9.739608'},\n",
       " {'date': '2020-06-02', 'profit': '11.386556'},\n",
       " {'date': '2020-06-09', 'profit': '10.99783'},\n",
       " {'date': '2020-06-16', 'profit': '10.92307'},\n",
       " {'date': '2020-06-23', 'profit': '10.508111'},\n",
       " {'date': '2020-07-02', 'profit': '10.198157'},\n",
       " {'date': '2020-07-09', 'profit': '15.540353'},\n",
       " {'date': '2020-07-16', 'profit': '12.003112'},\n",
       " {'date': '2020-07-23', 'profit': '15.002095'},\n",
       " {'date': '2020-07-30', 'profit': '15.834449'},\n",
       " {'date': '2020-08-06', 'profit': '16.528257'},\n",
       " {'date': '2020-08-13', 'profit': '15.734118'},\n",
       " {'date': '2020-08-20', 'profit': '15.53694'},\n",
       " {'date': '2020-08-27', 'profit': '15.379843'},\n",
       " {'date': '2020-09-03', 'profit': '16.733311'},\n",
       " {'date': '2020-09-10', 'profit': '15.128788'},\n",
       " {'date': '2020-09-17', 'profit': '15.090954'},\n",
       " {'date': '2020-09-24', 'profit': '13.361952'},\n",
       " {'date': '2020-10-09', 'profit': '13.039517'},\n",
       " {'date': '2020-10-16', 'profit': '13.583121'},\n",
       " {'date': '2020-10-23', 'profit': '15.631248'},\n",
       " {'date': '2020-10-30', 'profit': '12.650589'},\n",
       " {'date': '2020-11-06', 'profit': '13.209543'},\n",
       " {'date': '2020-11-13', 'profit': '13.185384'},\n",
       " {'date': '2020-11-20', 'profit': '12.162153'},\n",
       " {'date': '2020-11-27', 'profit': '12.89317'},\n",
       " {'date': '2020-12-04', 'profit': '12.555912'},\n",
       " {'date': '2020-12-11', 'profit': '10.931681'},\n",
       " {'date': '2020-12-18', 'profit': '9.176007'},\n",
       " {'date': '2020-12-25', 'profit': '6.997812'},\n",
       " {'date': '2021-01-04', 'profit': '8.486986'},\n",
       " {'date': '2021-01-11', 'profit': '7.24934'},\n",
       " {'date': '2021-01-18', 'profit': '8.134852'},\n",
       " {'date': '2021-01-25', 'profit': '7.143159'},\n",
       " {'date': '2021-02-01', 'profit': '5.139498'},\n",
       " {'date': '2021-02-08', 'profit': '4.934661'},\n",
       " {'date': '2021-02-22', 'profit': '8.045578'},\n",
       " {'date': '2021-03-01', 'profit': '8.869353'},\n",
       " {'date': '2021-03-08', 'profit': '9.020388'},\n",
       " {'date': '2021-03-15', 'profit': '13.016504'},\n",
       " {'date': '2021-03-22', 'profit': '15.724058'},\n",
       " {'date': '2021-03-29', 'profit': '15.354489'},\n",
       " {'date': '2021-04-06', 'profit': '15.259541'},\n",
       " {'date': '2021-04-13', 'profit': '16.714527'},\n",
       " {'date': '2021-04-20', 'profit': '19.942308'},\n",
       " {'date': '2021-04-27', 'profit': '27.508927'},\n",
       " {'date': '2021-05-07', 'profit': '28.48668'},\n",
       " {'date': '2021-05-14', 'profit': '30.180135'},\n",
       " {'date': '2021-05-21', 'profit': '30.566334'}]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "s='2018-01-02 00:00:00 [INFO] 20180102: 最高市值 1000000 , 当前市值 1000000收益率 ： 2.815944% , 最大回撤 0.0%'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2018-01-02'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m=re.search('(.*?) .*?收益率 ： (.*?)%',s)\n",
    "m.group(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.815944'"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.group(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.DataFrame(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>1.94858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>0.685567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-23</td>\n",
       "      <td>1.654852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2.334265</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date    profit\n",
       "0  2018-01-02         0\n",
       "1  2018-01-09   1.94858\n",
       "2  2018-01-16  0.685567\n",
       "3  2018-01-23  1.654852\n",
       "4  2018-01-30  2.334265"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 165 entries, 0 to 164\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   date    165 non-null    object\n",
      " 1   profit  165 non-null    object\n",
      "dtypes: object(2)\n",
      "memory usage: 2.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['profit']=df['profit'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.set_index('date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>profit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-09</th>\n",
       "      <td>1.948580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-16</th>\n",
       "      <td>0.685567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-23</th>\n",
       "      <td>1.654852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-30</th>\n",
       "      <td>2.334265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-20</th>\n",
       "      <td>19.942308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-27</th>\n",
       "      <td>27.508927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-07</th>\n",
       "      <td>28.486680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-14</th>\n",
       "      <td>30.180135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-21</th>\n",
       "      <td>30.566334</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>165 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               profit\n",
       "date                 \n",
       "2018-01-02   0.000000\n",
       "2018-01-09   1.948580\n",
       "2018-01-16   0.685567\n",
       "2018-01-23   1.654852\n",
       "2018-01-30   2.334265\n",
       "...               ...\n",
       "2021-04-20  19.942308\n",
       "2021-04-27  27.508927\n",
       "2021-05-07  28.486680\n",
       "2021-05-14  30.180135\n",
       "2021-05-21  30.566334\n",
       "\n",
       "[165 rows x 1 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 165 entries, 0 to 164\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   date    165 non-null    object \n",
      " 1   profit  165 non-null    float64\n",
      "dtypes: float64(1), object(1)\n",
      "memory usage: 2.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAIAMOjUyIY/boZqyIruXklUIpwAAAACQQalOvcYYu5eSVQinAAAAAJBBp0aDdOqdAeEUAAAAADKoa2SCTr0zIJwCAAAAQIYEwlGNBCN06p0B4RQAAAAAMoROvbMjnAIAAABAhqRmnBJOz0U4BQAAAIAMOTVVOaUh0tkIpwAAAACQIadGgipyOlRXXmz3UrIO4RQAAAAAMqRrZEJN1R45HMw4PRvhFAAAAAAypGt0gvOmsyCcAgAAAECGnBqZYIzMLAinAAAAAJABoUhMA76wllbTDGkmhFMAAAAAyIBuZpzOiXAKAAAAABnQlQynSwmnMyKcAgAAAEAGdI0kwylnTmdEOAUAAACADDg1MiGnw6ipymP3UrIS4RQAAMAGPWMT+qd79ykcjdm9FAAZ0jU6ocZKj1xOYthM+LcCAABgg3uf6dY3/nBCO48P270UABnSNTLBedM5EE4BAABssKdrTJK068SIzSsBkCmnRoJaxnnTWRFOAQAA5sGyLN23p0cDvnBa7pcKp+0nqJwChSASi6t3PETldA6EUwAAgHn47f4+/eV3n9JN//6IvvPkScXj1kXfa2wiopNDQRW5HHqmc1SRWDyNKwWQjXrHQopbzDidC+EUAADgPCzL0hcfPaql1SXa0FylD/1sr/7kC3/Q/u7xi7rfvmTV9PZNzQpOxnSg5+LuAyB3nJoaI1Nq80qyF+EUAADgPNpPjujpjlG984aV+t47rtKnX3eFOoeDeuV/PaGP/nK/RoOTF3S/1Jbet127QhLnToFC0DWaDKdUTmdFOAUAADiPLz16VN5St+7Y0iJjjF6zeZkefO8NunNri776xHFd+7GH9H9+fUD946F53W9P15iWeUu0rqlSS6tLtPsk506BfHdqJChJaq5mxulsCKcAAABzONzn0+8O9OstL2hTSZFz6vHq0iL9259cpvvf80LdvL5B//34MV338Yf1wZ/s0cmhwJz33NM1psuWVkmStrV5tevEiCzr4s+wAsh+XSMTqq8oVrHLef6LCxThFAAAYA5ffuyYPG6H3nxN24zPr22s1Gdev1kPv+9Feu3WZfrx7lO6+VOPznqONNUMaWMynG5pq9GAL6zO4YnF+i0AyAJdo8w4PR/CKQAAwCx6x0L62TNdet3WFtWUFc15bWttmf7Pay7TQ++7QZYl3fts94zXpZohTa+cStIuRspkvUO9Pn36geepcuOinBqZ0DIvzZDmQjgFAACYxdd/f1yxuKU/f+HKeX/NMm+prlpZowf29834/J6zwuml9RWq8LjUzrnTrPelx47qMw8e1rHBubdtA2fzhSLqGp1QWy3hdC6EUwAAgBmMhyL67o4OvfzyZrXUXNgbypvXNehIv1/HZwgxqWZI3mQl1uEw2tLqVTsdexdFumbIxuOWHj00IEnacYwPEnBhnjw2rFjc0jWrau1eSlYjnAIAAMzgezs65A9H9c7r5181TbllfYMk6YH9vec8N70ZUsq2thod7vdf8EgazO3hQ/268qMPqD0NW6afPTWqoUDiv8+O40MLvh8Ky+OHB1TidmpLq9fupWQ1wikAAMBZIrG4vvbEcV13yZKpxkUXYpm3VOuaKvW7/f1nPH52M6SUrck3rLtPUj1Nl8loXP/7F/vlC0X17799fsH3e/jQgBxGeuHqJdpxbJhzp7ggTxwe1FUra+jUex6EUwAAgLMc6vWp3xfWndtaLvoet6xvUPvJYQ0HTldDz26GlHJFS7XcTqNdbO1Nm2/98YSODwZ087p6/fHYkHYeX1j19OGD/bpyuVcv2dCo3vGQOoaD6Vko8t6pkaCODQb0wtV1di8l6xFOAQAAzrI/OQZmY3PlRd/jlnUNilvSgwdON0Y6uxlSisft1MalVWnZfgppODCp/3zwsK6/tE6fvetKLSkv1mcevPjqaf94SHu6xnTj2npdvaJGEudOMX9PHB6UlKi6Y26EUwAAgLPs7x5XaZFTrbVlF32PjUsr1VTlOaNr79nNkKbb1laj506NKRSJXfRrIuE/fve8ApMxfejl61RS5NRf3LBSvz8ydNHjeh5JNkK6cU29LqkvV21ZkZ7k3Cnm6fHDg2qoLNbq+nK7l5L1CKcAAABnOdAzrjWNFXI6zEXfwxijm9c16PHDg1OBc6ZmSClbWr2ajMW1N1ldxcV5vs+n7+7o0BuvWq5LGyokSW+8qjVRPf3d4Yu658OH+tVU5dG6pgoZY7R9RQ2VU8xLLG7p90cHdd0ldTLm4r+fFArCKQAAwDSWZWl/z7jWN138lt6UW9Y3aCIS0++PDM7aDCkl1RSpnaZIF82yLH30l/tVVuTUe26+dOrxkiKn3nn9Sj1xZPCCt05PRuN6/PCgXrSmfipcXLWiRl2jE+rk3CnOY2/XmEaDEV1/KVt654NwCgAAME3X6IR8oajWpSGcXrWyRuXFLj2wv2/WZkgpteXFWrmkjHOnC/DIoQE9fnhQ775ptWrO2jr9xquXa0l5kT7z4IVVT9tPDMsfjurFa+unHrtqZWJW5Y4FNllC/nviSOK86bWXEE7ng3AKAAAwzf7uRDOk9QtohpRS7HLqhjV1+t2Bfj17au5wKklb27xqPzmieJwxJRcqEovrX361XyuWlOnN17Sd83xpkUt3X79Sjx8e1O6T8w+VDx3sV5HToResqp16bE1DhapL3dpxjHOnmNtjzw9ofVOllpQX272UnEA4BQAAmOZAj0/GSGsbK9Jyv5esb9CgP6wf7OqYtRlSynWr6zQajOh/njqVltcuJD99uktHBwL64G1rVeSa+S3un17dqtqyIv3HBZw9fehQv65aWaOyYtfUYw6H0ba2GiqnBciyrHnPuA2Eo3qqY0QvZEvvvBFOAQAAptnfM6YVtWUqLXKd/+J5eNGl9XI5jE4OBeesmkrSKy5r0vYVNfroL/arZ2wiLa9fCGJxS1985KjWN1XqlvUNs15XWuTSO29IVE/f8rWdeqpj7vO9J4cCOjYQOGNLb8pVK2rUMRzkv1OB+cvvPKU3fGWHxkOR81674/iQIjFLL7yE+abzRTgFAACY5kCPLy3nTVOqSt3anpyNOVszpBSHw+gTr71c0bilD/x4z7wrNIXuN/t6dWwwoL++8ZLzdkT9s2tX6P23rtVzp0b1J5//w5wh9eGD/ZI0Yzi9OnXuNANdez/120P60qNHF/11cH47jg/pj8eGdNeXn9SgPzzntY8fHlSxy6Gtbd4MrS73EU4BAACSfKGIOoaDaTlvOl2qmne+yqkktdaW6f23rtGjzw/oR+2Ftb03Hrf0T/fu0+E+37y/xrIsfe7hI1q5pEy3bmw87/Uup0N/+aJVeuL9L9YHblurPV1j+pPP/0Fv+uoOPbC/T9FYfOrahw4NaGVd2Yzzbtc1VarC49KORZ53almWvrOjQz9/pntRXwfnNxqc1EgwopvXNejogF93fvGP6hqdvXL++OFBbV9RI4/bmcFV5jbCKQAAQNLB3kQoWteUnvOmKXdubdH/94r1ZzTVmcubr2nTVStq9NFf7lf3HG9+pwtFYnO+Uc4F/b6wvvGHE/r1nt55f81jhwe1r3tcf3HDqguaS1tW7NJf3LBKj//DjfrgbWt1sNend3yrXdd+/CF96reHdLjPpyePDenGNedWTSXJmTp3usiV097xkIYDk+ocDlJJt9nxwYAk6fXbWvTtt1+lAV9Yd3zhDzo24D/n2p6xCR3p9+v61WzpvRCEUwAAgKRUp950buuVEkHo7detkMs5v7deie29VyS29/7k/Nt7Q5GY3vCVJ3XjJx/J6VE0I8FJSbqgc5yfe/iImqo8un3z0ot6zbJil955wyr94QMv1pfetEXrmyr12YeP6JZPP6bJaHzGLb0pV62o0bHBgPrHQxf12vOxryvxZ9IXjmo0eP5zjlg8J4YS4XRFXZm2tdXo+3dfrXA0rju++Ef9Zl/vGedQHz+cGCFz3WqaIV2I9Jz0BwAAyAMHesblLXWrsdJj91K0vLZUH7htrT5y7z7d096p121bPuN18bilv7vnGT3dOar6imK941vt+ulfXau2JeduRc12p8Pp/MJe+4lh7Tw+rA+/Yv2sHXrny+106KUbGvXSDY06NRLUPe2n1Dkc1La2mlm/Zvq801de0byg15/N3u6xqZ93DAfn7PaMxXV8ICCHkVq8pZISZ8jv+Ytr9Oav7tQ7v71bDpP4YGtbW432dY9pSXlx2rp+F4q0VE6NMV8zxvQbY/ZOe+yfjDFdxphnkv+8LB2vBQAAsFj294xrXVPleZvqZMqbrm7V1Str9M+/2K+fPd014zUfv/+gfr2nV//rZev0w7uvkTFGb/36Tg0HJjO82oVLVQbnWzn9/CNHVVNWpNdvb0nrOpZ5S/V3t1yqT79u05yhd2NzpcqKnHpyEeed7usen1pDx3Bw0V4H53d8KKhl3tIz/kysqivXg++9Qd97x1V6902rVVXi1g92dWjXiRHduKYua76X5Ip0VU6/Iem/JH3rrMc/bVnWJ9P0GgAAAIsmGovrUK9Pb7q61e6lTHE4jD7z+s366+8+pff88Bk9dLBfH331RlWVuiVJ337ypL702DG9+ZpWvf26FTLG6Ctv3qK7vrJDd3+rXd/586tyqhnLhVRO93eP66GD/XrvLZembezPhXI5HdraVqMHD/Rrmfeo6iqKVV9RrLqKYrXWlqZlXfu6xnT96jr97kAf4dRmJwYDWjHDjgSP26kXrFqiF6xKbOGdjCa+l7QuKc30EnNeWiqnlmU9Jil3DzgAAICCd3wwoHA0nvbzpgvVUOnRD+6+Wu97yaX69Z4e3faZx/THo0N6+GC/PvLzvbppbb0+/Ir1UxWaLa01+vSdm9R+ckR//z/PKR7PnSY6qcqpLxSVPxyd89ovPHpU5cUuvfmatgysbHav2bxU/nBUH7//oN73o2f15q/t1G2feVwv/Y/HFtzAaDgwqe6xkLav8GpJeZE6Cae2sSxLx2cJp2crcjl02bIqVXrcGVhZflnsj5neZYx5s6R2Se+1LGvuSccAAAA22d+TaDyT7jEy6eByOvSuF6/WC1fX6T0/fEZv+O8nVeR0aF1Tpf7zrs3nNFp6+eVN6hxZq4/dd1At3hL9w61rbVr5hRmZthW5Z3RCqxtmPq/XNx7Sr57r1juuXzlVRbbL7ZuX6vbNSxWcjGrAF1a/L6xf7+nR139/QieHggs6+7sved50Q3OVWmpKqZzaaNA/KX84qrZaqqGLaTG79X5B0ipJmyT1SPr3mS4yxtxtjGk3xrQPDAws4nIAAABmt79nXG6n0aq6cruXMqsrWqr1q3dfpzdsX65VdeX62lu3qax45lrDO69fqbu2t+jzjxzVw4f6M7zSizMyrRvtXFt7D/X6FLekF88y5sUOpUUutdYmuri+Ptm8avfJhdVl9iW7R29ortRywqmtUmNkVmTx94d8sGjh1LKsPsuyYpZlxSV9RdL2Wa77smVZWy3L2lpXxxwgAABgjwM9Pq2ur1hw19fFVlrk0r++5jL9+m9fqIY5ugobY/SRV27Q2sYK/f2PntWAL5zBVV6c0eCkKj2JsD1XU6RUSFuepVWs1fXlqvC41J6GcLq0ukTVpUVaXlOq7tEJRWLxNK0SF+JEKpzW5l4X7FyyaN99jTFN0375Gkl7Z7sWAADAbvu7x7PuvOlCedxOfeb1m+ULRfW+Hz2b9edPR4KTWttYKWOk7tHZK6edw0EVOR1qqLB/5M9MHA6jK5d79dRCw2nXmDYkt5m31JQqbkndo/OfAYv0OT4UkNtp1FydnX/m8kW6Rsl8X9IfJa0xxpwyxrxd0v81xuwxxjwn6UZJ/286XgsAACDd+n0hDfrDWXnedKHWNFboQy9fp0efH9A3/nDC7uXMaTQYUV1lsZaUF6t3jm29nSNBLaspkcORvWM6trZ69Xy/T2MTkfNfPAN/OKrjQwFtXFolSVpek6gSs7XXHscHAlpeU3rO+W6kV1oaIlmWddcMD381HfcGAABYbAd6fJKkdU0zN+DJdX96dasefX5AH7vvoK5ZVZu1FeLRiYi8pW41V3nUfZ5tvS3e7NzSm7Kl1SvLkp7uGNGLLuJs7IGecVmWpiqnhFN7nRiaX6deLAzRH12YjdQAACAASURBVAAAFLwDqU69WRraFsoYo4//P5erqtStd3//aU1Mxuxe0jnicUujwUl5S4vUWOWZs3LaMRScCmvZatPyajkd5qKbIu3rOt2pV0qMFCpyOtQ5zLbeTIvH5z9GBgtDOAUAAAVvf/e4mqs8qi4tsnspi6a2vFifuvMKHe736+P3H7R7OefwhaKKW1J1aZGaqkpm7dY7FoxoPBTN+nBaWuTS+qbKiw+n3eNaUl6khspiSZLTYbTUW8KsUxv0jocUjsYXNBYI80M4BQAABe9AT/41Q5rJC1fX6eWXN+m+vT12L+UcI8HEjFNvqVvN1R75w1GNh849r9k5kghnLVkeTqXE1t5nOkcVvYgOu3u7x7W+uUrGnD5Xy6xTe9CpN3MIpwCQx776xHHtOTVm9zKArBaKxHR0wF8Q4VSSVi0pU78vnHUjSU6H0yI1VpVI0oxbe1PhrKWmJHOLu0hbWr0KTsZ0sNd3QV8XjsZ0uM+njWc16FpeU0I4tcGxqRmnhNPFRjgFgDwVi1v611/t1/d3ddi9FCCrHRsIKG5JlzbmZzOkszVVl8iypP4sm3s6GkxUSauTDZGkmcemnA6nuVE5laT2E8MX9HXP9/oVjVtT501TlteUamwiorHgxXUAxsU5MRiQx529o4vyCeEUAPLUcGBScUvqH8+uN6BAtjky4Jckra4vt3klmdGYDH69c3TDtcOZldPUGmeunHpL3ar0uDO6vovRXF2i5iqP2i/w3Om+7lQzpLMrp4lAntrajMw4PhhQW21ZVo8uyheEUwDIUwPJqki/b/aOlwCkI30+OYwKphNnc3LLbPdodn1vGJlWOW2o9MgYqXuGcNo5nP2deqe7stWrpy4wnO7tHlNFseuc32cL42RscZwxMhlDOAWAPDXgT4TTvvHsegMKZJsjA34trymVx+20eykZ0VSdqEr2ZFnldDQ4KYeRKj1uuZ0O1VcUq2eGbb2dw0Ety6FwurXVq+6x0IxblGezr3tc65orz6nUEU4zLxqLq3M4SKfeDCGcAkCeSlVOB/2TisUtm1cDZK8j/X5dUiBbeiWpotilsiLnrKNa7DISnFRViXsqkDVWlaj3rA/XYnFLp0YmcqpyuqW1RpLmPVImFrd0oGdcG886byolgru31E04zaCu0QlFYhaV0wwhnAJAnkqF01jc0lCAc6fATKKxuI4PBnRJfWE0Q5IkY4yaqkvUk4Xber3T5sw2V3nOqTb2jE0oGrdyKpyua6pQids573B6bMCvUCR+znnTlOU1pcw6zaDjqU69hNOMIJwCQJ4amNaJk6ZIwMxODgcViVkFVTmVpKYqj3qybMv/aHBS1aWnmxw1VZWoZywkyzq986NzOBFWcymcupwObWqpnnc43dc9LknasHTmcMqs08xKhdM2ZpxmBOEUAPJU6sypxLlTYDaH+wqrU29KU5VnxvOcdhoJnFk5baryKDgZ03goOvVYqmLY4s2dcCpJW9u82t8zrkA4et5r93aNqdjl0CV1M/+ZXF5Tqq6RCUWzbE5tvjoxGFBFsUtLyovOfzEWjHAKAHlqwBeaGlLfR+UUBepNX92hH+ycfdbv0eQYmVUFF05LNOAPazKaPQEnUTmdFk5naNzUMRyU02GmnssVV7Z6FYtbevbU6JzXBcJR/XZ/n9Y3V8rlnPlt+vKaUkXjVtadGc5Xx4cSzZCMYYxMJhBOASBPDfjCWtdYKWMYJ4PC5A9H9fjhQf38me5Zrznc51NzlUflxa4Mrsx+TVUeWVZ2fW9InDk9c1uvpDNCWMdwUM3VHrlnCW7Z6srlXknS7hNzb+39yL371DkS1PtvXTvrNVOzTtnamxHHB/106s2g3Po/GwAwbwO+sJqrS1RbVkTlFAWpYyjx5v2ZzlFFZtkCeWTAX3BVU0lqqj43+NkpFIlpIhKTt+zMbb2Szmjc1DkSzLktvZJUVeLWpQ3l2nlieNZrfv5Ml/5n9yn9zY2X6OqVtbNexziZzAlHY+oamaAZUgYRTgEgD4UiiXNadRXFqq/wqJ8zpyhAqTfvE5GYDvSMn/N8PG7pSL9fqwuoU2/KVPDLknA6GoxI0hkNkeoriuUwZ27r7RwO5lQzpOluXFuvxw8P6p9/se+c86IdQ0H9r5/u1ZZWr9590+o579NU5ZHLYQinGdA5HFTcklYsyc0/c7mosPawAECBGEw2Q6orL1ZDZbH6smjrHpAp07c9tp8Y0eXLqs94vmt0QqFIvOA69UrTq5LZ0RRpdGJSks5oiORyOlRf4ZkK0IFwVIP+yanKYa75+5es0WQ0rq///oQO9/n1X2/YrOrSIkVicf3ND56Ww0ifef2mWc+apricDi31lswYTn/1XI/294ypwuNWpcetyhKXKj1ubWn1qqzAtq6nw/HBxL9jOvVmDn9KASAPpcbI1FUUq6HSo73d51aNgHx3cjigSo9LFR63dp8c0Z9dt+KM548kmyGtbii8cFrhcaui2JU1ldORwLmVUynRFClVOe0cSQSFXK2cupwOfeSVG7SuqVIf+ulevfpzv9dX3rxVP326S892jurzb7xSy+a5ZXmmWaePPT+gv/7eUzJGmjZ9R5J0x5Zl+sQdV6Trt1IwTjDjNOMIpwCQh6aH0/pKj4b8YUVj8fN+Ig/kk47hCbXWlmnFkjLtOD4ky7LO6Lh5JDlGZraRHfmuscpzxpZZO40Gz62cSlJzVcnUluzUjNNcrZym3Lm1RavqyvXOb+/W7Z/7vSYiMd21fbledlnTvO/RUlOq+/b0TP16ODCp9/7oWa2uL9e977pOliyNT0TlC0X0nw8d0S+f69GHX7leFR73HHfF2Y4NBuQtdZ/RRRqLi3cpAJCHUjNOE2dOixW3pKHApM2rAjIrdT5xa5tXfeNhdZ21hfVIv19LyovOaMJTSJqqS7Kncpo8c3p2OE0E6JAsy5raxpqrldPptrR69Yu/uVarGyq0rrFSH37F+gv6+uU1pRoJRjQeisiyLH3gx89pLBjRf7x+k0qKnCotcqmxyqPVDRX6s2vbNBGJ6RfP9pz/xjjDyaEAnXozjHAKAHlowBeWMVJNWZEaKhNny/poioQCEotbOjUSVEtN6ekxHifPHONxuN+nVQVaNZWkpkpPFoXTxIdn52zrrfJoIhLT2EREncNBlRe7zhg3k8uaqkr0s796gX7xN9eppMh5QV87fZzMPe2d+u3+Pv39S9doQ3PVOdduaqnWpQ3luqe9c9b7WZalrz5xXHu7xi7sN5HnesdDU+ezkRmEUwDIQwO+sGpKi+R2OtRQWSxJjJNBQekZm1AkZqm1tlRrGytUVuRU+7QZk5aV7NRbgOdNU5qqPRr0hzUZnXnMTiaNBidV4nbK4z4zpDVPG3nTMZz4sGH61uxcZ4yR03Hhv59UOH3s+UH98y/269pLavX2s85UT3+NO7e26JnOUT3f55vxmvv29uqjv9yv137xD7p/b+8FrydfDYyHVV9BOM0kwikA5KEBX1h1FYlQSuUUhWj6FlCX06HNy71qn1Y5HfCFNR6KFux5UylxntOysuN7w0gwck7VVEps65USHzZ0DgfV4i3J9NKyUurc7Sd/e0hup0OfvOMKOeYIua/ZvFRup9EPd51bPY3E4vrEbw7pkvpyrW2s1F9+d7e+9OhRWWd3VSowwcmofOGo6pMf8CIzCKcAkIcG/KfDaW1ZkRxG6vdROUXh6DzrfOKWVq8O9Y7LF0qcbTzSn+rUW3gzTlMas2jW6WhwcsamM81ViTDaNZqonObDedN0qCpxq6rErVjc0r/9yWVqqpo7tNeWF+vmdQ366dNd51TKf7CrU8cHA/rgbWv1g7uv1ss2Nunf7juof/zpHkVi9lfV7dKf3G1E5TSzCKcAkIcGfGHVlSfCqcvpUG15sfqzoDoCZMrJoaBcDjN1Xmxrm1dxS3q6Y1SSdDgZTgtxxmlKc/XpqqTdRoKRGc+S1lUUy+kw2nNqVOFoXMtrCacpt6xv0J9du2LeXX7v3Nai4cCkfnegb+qxQDiqz/zusLa31ejFa+vlcTv12bs26103XqLv7+zUW7++U/5wdLF+C1kt9YFuA5XTjCKcAkCesSzrjG29UuIv12zYugdkSsdwUEu9JVPjkzYv98phNLW190i/XxUel+orCveNZ2PV6fOcdhsJTp7TqVeSnA6jhopi7Tw+LCn3x8ik0yfvuEIffuX8u/xev7pOTVWeM7b2/vfjxzXoD+v9t62dOsvrcBi976Vr9InXXq7fHxnSd548mfa154J+X+L/CyqnmUU4BYA84wtHFY7GzwynFR4aIqGgdJ61BbS82KW1jZXafTIRcg73+3RJfXleNde5UOXFLlV4XOoZtb9yOjrLmVMpMfLmxFBim3aLl3B6sZwOo9duWabHDg+oe3RCg/6wvvzYUd26oVFbWr3nXH/H1hZdUl+uJ48N2bBa+/VNbest3A+w7EA4BYA8M+A7PeM0pb7SM/UpMFAITiY7u063pdWrpztGFY3FdaQ/oNUFvKU3panK/nEy8bil0Vkqp9Lps7GStIyGSAtyx5YWWZb0492n9NkHDysUjevvb10z6/XbV9So/cSIYvHCa47U7wupyOmY9UMTLA7CKQDkmalwWn7mtt6hwGRBN7dA4RibiGg0GFHrWeF0a5tXwcmYdhwf1qA/XNDnTVOaqkpsD6e+UFRx69wZpynNyXDaWOk5Z9QMLszy2lK9YFWtvv3kSX13R4det61lzlm/V62okT8c1YGe8QyuMjsMjCeOxxTy7go7EE4BIM/MVDltqPTIsqRBP1t7kf/O7tSbktq6+IPkmbvV9YXbqTeludpje0OkkeCkJM1aOU11oqVTb3q8bluL+n1huZ0Oveem1XNeu31FjSQV5NbePl+IMTI2IJwCQJ6ZcVtv8uecO0UhSIXTs7f1Lq0uUWOlR7/Z2yupsDv1pjRWlmjQP6lwNGbbGqbCadksZ06TldNlNWzpTYeXbmhUc5VH73rxJaqvnLvZT1NViZbXlE41pCok/eNhzpvagHAKAHlmwB+W22lUVXL6jV5D8g0IHXtRCE6mKqdnjR0xxmhLm1eTsbg8boeWVhN2mpLjZPrG7PvgajSYmD0705xTKdEQSaJymi4et1O//8CL9VcvWjWv67evqNGuE8OKF9i5035feOrvTmQO4RQA8kxqxun0czKprUnMOkUh6BgOylvqVqXn3Erc1uTW3lV15XI4OEuWqkraubV3dGLubb0rlpSprqJY29pqMrmsvGaMmfdZyu0rajQSjOjIgH+RV5U9QpGYxiYiVE5t4LJ7AQCA9Dp7xqkk1ZYlBtmnhooD+ezsMTLTbW1NBBy29CY0ZcGs05FAonLqnaUhUlWJW7v+182ZXBKmuXpFrSRpx7EhXdpQGOe0U8djmHGaeVROASDPzBROnQ6juvJitvWiIJwcCmp5bdmMz61rqtDKJWW6dtWSDK8qO52unNr3vWE0OCmH0YyVbtivpSZxVntHAZ07TY1eoyFS5lE5BYA8M+AP64qWqnMer68spiES8l40FlfX6IReeUXTjM+7nA499L4XZXZRWays2KVKj8vWbb0jwYiqStxss85SxhhtX1GjJ48NybKsghitkvq7kspp5lE5BYA8EotbGvKHz5hxmlJf4aFyirzXMxZSLG7RPOcCNFeXqHvUxm29wclZz5siO1y1skb9vrBODAXtXkpGpPozUDnNPMIpAOSR4cCk4pbO2dYrSQ2VxZw5Rd7rmJpxOvO2Xpyrscqj3nEbGyIFI6qe5bwpssNVyXmnO48XxrzTfl9YLodRDR+aZBzhFADyyEwzTlMaKj0aDkxqMhrP9LKAjDk5NPMYGcyuqapEPTZXTmcbI4PssKquXLVlRQVz7rRvPNG7ga3mmUc4BYA8MuCfK5wWn3ENkI86hoNyO40amU84b81VHg0FJhWKxM577befPKnvPHkyra9P5TT7pc6d7iyQcNrvCzFGxiaEUwDII1OV0/Jz35inGjtw7hT5rHM4qBZvqZxUPOatsWp+3xticUv/976D+tDP9upTDzwvy7LS8vqcOc0N21fU6NTIhLpG7dsCnikDvrDq+YDLFoRTAMgjqXC6pOLcN3qpxg79hFPksZPDAbXQDOmCNFcnZp2erynSgZ5x+cJRra4v138+eFif/O2hBQfUcDSm4GRs1hmnyB7bC+jcad84lVO7EE4BII8M+MIqK3KqtOjcSWENlanqCNt6kb86hoJ06r1Aqcrp+Zoi7TqR2NL59bdt013bW/S5h4/qY/cfXFBAHQ1GJIkzpzlgbWOlKj2uvN/aOxmNayQYYYyMTZhzCgA5qHt0QmVFLlWdVW0Y8IdnPG8qSTWlRXI5zNRwcSDfjAUjGg9F1UozpAvSXDW/yunO48NaWl2iZd5S/evtl8npMPrSo8cUjVn60MvXXdT8y5HgpCSxrTcHOB1G29pqtONYfofTVF+GBsbI2IJwCgA56K1f36ml1SX6+tu2n/H4gC80azh1OIzqK4qpnCJvpcbIsK33wpQUOVVd6lbv2Ozh1LIs7ToxrOtX10lKfD/56Ks3yuVw6KtPHNeuE8Pa1FKt9U2V2tBcpdUN5fK4ned97ZFAonLKtt7csH1FjR482J9sGJSflcU+ZpzainAKADnGsiydGAzqcL8/0fxl2hvxAV9YaxorZv3a+koPDZGQt04OBySJbb0XobHSo56x2bf1HhsMaNA/qW3Jc4dSooPrR165XkurS/Tb/b368e5T+tZkouOvy2H09utW6AO3rZ2zojqarJyyrTc3pM6d7jo+opdf3mTzahZHf/ID3HwN39mOcAoAOWY4MKnJWGJW6T3tnXrvS9ZMPTfgC+u6S5bM+rX1FcVTcyCBfJOqnBJOL1xrban2do3LsqwZw+Su5DnD7dPCqZQIqO+4fqXecf1KxeOWOoaD2t8zrt/s69WXHjsmp8PoH25dO+vrjiTPnHrLqJzmgo1Lq+RxO7T7ZP6G0wEflVM70RAJAHJMT3LrXVmRUz/c1aloMqiGIjGNh6KzbuuVEk2R+jhzijzVORzUkvIilRXz2fuFunldg7pGJ/R05+iMz+88Mawl5UVauaRs1ns4HEZtS8r0ssua9B+v26S7ti/X5x85qs89fGTWr+HMaW5xOx26fFm1dneM2L2URdM3HpbDSLVlhFM7EE4BIMekzoW97doV6veF9dDBfknSYLKJw9zhtFijwYjC0djiLxTIsJNDQc6bXqSXbmxUkcuhe5/pnvH5nceHta2tZt5Nj4wx+pfbN+r2Tc36xG8O6WtPHJ/xurGJiDxux7zOpyI7XLncq/3dYwpF8vPvkX5fSEvKi5mVbBPCKQDkmNS5sDdctVwNlcX6/s4OSadnnM4VTlNDxftpioQ8Y1mWjg0E2NJ7kSo9bt24pk6/2tOjWPzM0TDdoxM6NTKhbW01s3z1zJwOo0/ecYVeuqFB//uX+/XDXR3nXDMSmKRqmmO2tHoViVna0zVm91IWRb8vzJZeGxFOASDH9IyF5HIYNVR69LqtLXrk+QF1jU6cDqflszdxSM06ZZwM8s3+nnH1jod0zcpau5eSs151xVIN+MJ68tjQGY+n5puefd50PlxOh/7zrs26/tI6feAne6Y+TEsZCUZohpRjrlxeLUnafTI/t/b2jYfVQDMk2xBOASDH9I6F1FDpkdNhdOe2FknSD3d1Ts1mm7NymnyOcTLIN/fv7ZXDSLesb7B7KTnrpnX1KitynrO1d+fxYVUUu7SuqfKi7lvscupLf7pF112yRB/8yR598Cd7po4WjAYnGSOTY2rLi9VWW6qn8jScDvhCVE5tRDgFgBzTMxZSY1XiU91l3lLdcGmd7tnVOXUWtbZ89ipEqnI61zxDIBf9ek+Prl5Zq9py3lReLI/bqZdsaNR9e3vOOJe+8/iwtrR5F3QGr6TIqa+/dZv+8kWr9P2dHbrzi39U9+iERoJs681FV7Z69VTHiCzLOv/FOSQSi2soMKk6Kqe2SUs4NcZ8zRjTb4zZO+2xGmPMA8aYw8kfvel4LQAodL3jp8OpJN21fbl6x0P6yVNdqikrkts5+7d2b6lbzVUe/fipU+ecKwNy1eE+n44OBHTbxka7l5LzXnVFs8ZDUT32/KCkxJnQw/3+Cz5vOhOX06H337pWX/zTLTo6ENArPvuEukdDqqZymnO2tHo16J+cGt+ULwb9YVlWonkg7JGuyuk3JN161mMfkPSgZVmrJT2Y/DUAYAEsy1LP2ISaKk+H0xevrVd9RbG6RidUd56qkTFG//jyddrXPX7O2S8gV/16T6+MkV66gXC6UNetXiJvqVv3PpvY2ruQ86azuXVjo37+rmtVW1akiUiMymkOunJ5oub0VJ6NlEk1C6yncmqbtIRTy7IekzR81sOvlvTN5M+/Ken2dLwWABSysYmIQpG4mqpLph5zOx26c2vi7Olc501TXn5Zk65ZWatP/OaQhgOTi7ZWIFPu29ujra3eqW7UuHhup0O3Xdak3+3vU3Ayqp3Hh1XkcujyZVVpfZ1VdeX62V9fq7+75VK9dsuytN4bi+/ShgqVF7vyrilSvy8VTqmc2mUxz5w2WJbVI0nJH+sX8bUAoCD0JM+KNlWd+Sb8ddvmH06NMfrnV29QIBzVJ35zKP2LBDLo+GBAB3t9unVjk91LyRuvuqJZE5GYHtjfp10nhrWppVrFrvTPIS0rdundN61W25KytN8bi8vpMNrUUq2nTo7avZS06htP/B3bwAddtrG9IZIx5m5jTLsxpn1gYMDu5QBAVkvNOG08K5y21JTqo7dv1J9e3Tqv+1zaUKG3vqBNP9jVoedO5debCxSW+/b2SEpsFUV6bG+rUWOlRz/Y2am93eO6Ko1bepE/rmz16mDvuPzhqN1LSZt+X1jGSEvmaCyIxbWY4bTPGNMkSckf+2e6yLKsL1uWtdWyrK11dXWLuBwAyH2zVU4l6U1Xt2pL6/x7z/3tzatVW1asD/98n+I0R0KOun9vr65oqdbSaVvdsTAOh9ErLm/SH48NKRa30tIMCflnS6tXcUt6tjN/PuAc8IVUW1Yk1xyNBbG4FvPf/L2S3pL8+Vsk/XwRXwsACkLvWEgOo/M2PpqPCo9b//iytXqmc1T/s/tUGlYHZFbncFDPnRqjS+8ieNWmZkmJ7ZtXXsCHXigcm1qqJSmv5p32jYdphmSzdI2S+b6kP0paY4w5ZYx5u6SPSbrFGHNY0i3JXwMAFqBnLKT6Ck/aPtV9zeal2trq1cfvP6ixYCQt9wQy5Tf7eiWJcLoILltapZVLyrRxaZXKi112LwdZqKrErUsbyrU7jzr29vtCqmeMjK3S8t3Gsqy7ZnnqpnTcHwCQ0DsWOue86UIYY/RPr9qgV3z2Cf3smS695QVtabs3sNju29ur9U2Vaq2loU66GWP032/ZKocxdi8FWWxLq1e/eq5H8bglhyP3/6z0j4e1vqnS7mUUNDZUA0AO6RmbUHN1erccbWiulMth1O8LpfW+wGLqHQtp98kRvewyqqaLZWVdOZ10MafNy70aD0V1bNBv91IWLBa3NOgP06nXZoRTAMgRlmWpZyykxsr0Nn4xxqi6tEjDAbb1InektvQyQgawT6oJXz7MOx3yhxW3mHFqN8IpAOSI8VBUwcnYjJ16F8pb6tZocDLt9wUWy/17e7W6vlyX1JfbvRSgYK1cUqbqUndehNN+X1iSVEdDJFsRTgEgR/Qmx8ik88xpire0SMMBwilyQzxu6dlTo7r2kiV2LwUoaMYYXbncq6c6cn+cTN944u/YBhoi2YpwCgA5omdsQtLMM04Xylvm1ijdepEjTo1MKDgZ09rGCruXAhS8La1eHen35/zum1TltJ4zp7YinAJAjljsyulIjr+xQOE40DsuSVpLV03AdpuXJ+adPt2Z29XT/vHktt40zBHHxSOcAkCO6BkLyRgtSifB6mQ4tSwr7fcG0u1Qr0/GSJc2cN4UsNvGpVWSpAM94zavZGH6fCHVlBWpyEU8shNTlQEgR/SOhVRXXiy3M/1/cdaUuRWJWQpMxlRezF8NyG6Hen1aXlOq0iL+rAJ2q/S4tbS6RAd6fHYv5aLs7RrTj9o79YtnutVSU2r3cgoe39UBIEf0jIcW5byplKicStJIYJJwiqx3sHdcaxo4bwpki3VNlTqYQ5VTfziqH7V36p72UzrQM64il0Mv3dCod7xwhd1LK3i8AwGAHNEzOqGVdWWLcm9vKpwGJ/nkGFktFInpxFBQL7+M+aZAtljXVKGHD/UrFInJ43bavZzzevf3n9ZDB/t12dIqffTVG/SqK5aqqtRt97IgwikA5IzesdCijc6oKUv8pTxCx15kuSP9fsXiltY00gwJyBbrmioVi1s60u+fOoOarfacGtNDB/v1d7dcqnfftNru5eAsnPgFgBzgC0XkC0cXpVOvdHpbb66PAkD+O9ibONe2hjEyQNZIjXXanwNbez/38BFVeFx667Vtdi8FMyCcAkAOSA0HX6wzp6ltvcMBwimy26HecRW7HGqrZfs5kC1aa8tU4nbqYJY3RTrc59P9+3r11he0qdLDNt5sRDgFgBzQk5pxukjDwatK3DKGbb3Ifgd7fVrdUC7XInStBnBxnA6jSxsr5hwnE4nF9es9PYrH7RtZ9vlHjqrE7dTbrqXxUbbiOzsA5IBUOG2uLlmU+zsdRlUlbrb1Iusd6vVpTQPnTYFss76pQgd7x2edl/2LZ7v1V999Sg8e7M/wyhI6hoK699luvfGq5aopK7JlDTg/wikA5IDeZDitryxetNfwlhaxrRdZbSQwqX5feOp8G4DssbaxUiPBiPrGwzM+/8ThQUnS/Xt7M7msKV949Kicxugd16+05fUxP4RTAMgBPWMhLSkvUrFr8Vr0e0vdGmVbL7IYzZCA7JX60OhA77lbey3L0hNHEuH0dwf6FInFM7q2ivG4TwAAIABJREFU3rGQfrz7lO7YukwNi3Q8BulBOAWAHNAzNrFonXpTvKVFGmFbL7LYweSbXiqnQPZZ25TYbj9TU6Qj/X71+8J68dp6jU1EtOPYcEbX9pXHjylmWfqLG1Zl9HVx4QinAJADesdCaqxcnPOmKdWlRRphWy+y2KFen7ylbtVVLN72dgAXp6rEraXVJTM2RUpVTT9421qVuJ26f1/PrPe5f2+vtv7L79TvC6VlXcOBSX1vR4devalZLTV0+c52hFMAyAE9Y6FFGyOTUlPmplsvstrBXp/WNlbKGGP3UgDMYF2yKdLZfn9kUK21pVrdUKEXranTb/f1zdi117Is/f/s3Xd8W/W5P/DP0bItyfKQ947jON7OdAIZECDMAC1Q5oUWWqCFXtrS3vtry73dm9JeOmihhVL2KKsQIGGEgIFMJ45HvGLH25a8NCxrn98fHsTxiIdkHdmf9+uVF0Q6OudRArKe83y/z/OH9+rRY3XgxUNtPonpqX3NsLs9uOtcVk2DAZNTIiKJszndMA25kBjp3+Q0Uq3CkMsDu8vj1+sQzYXXK6Ku28L9pkQSlpOgwwnj4LifIy6PF/sa+7ApKwYAcFF+AgwWB460Dkx4/acnelHdaYZGJcdzB1t8Mnamot2EFXFaZMXxsyMYMDklIpK40U69/q6cRqmHW+tz3ylJUVv/EGxOD/ebEklYbqIOHq+IBoN17LFjbQOwOtzYPJKcbsuJg1IuYFfVxK69fy9tQoxWhR9dkY/WviF8fKJn3jG19tmQGsXlvMGCySkRkcSNJqf+3nMarVECAPoHubSXpGd0qSArp0TSlZM40rH3lH2npfW9EATgrEw9gOG9qWcvj8HblV3jZqI2GKx4v8aAmzdm4IpVSYhSK/HsgZZ5xSOKItr7h7jXNIgwOSUikrjOBaqcRo5UTgdYOSUJGh0jkx3P5JRIqjL0GoQqZWP/vwLD+00LkiIQpVGNPXZxQQJa+mzjjnvs4yaoFDL8x8Y0hCjkuGZtCnZXdcNomXxu6kyYhlywONxIifLvzV3yHSanREQS12kaAoAFGSUDAH1MTkmCarssSItWQxOiCHQoRDQFuUzAyvjwscrpoMONspb+sf2mo7bnxUMQhjvzAkCv1YGXDrfh6jXJ0GuHu3FfX5IGt1fEvw7PvTFSW//wz88ULusNGkxOiYgkrtNkR5RaiVCl3K/XiRpd1suOvSRBNV1mLuklCgK5iToc7zRDFEUcaOqD2yuO7TcdFaMNwfr06LF9p0/vb4HD7cWXNy8bO2Z5rBYblkXj2QNzb4zU2mcDAFZOgwiTUyIiiesy2ZEQ4f8frJFhIw2ROOuUJMbu8uBkrw25TE6JJC8nIRz9NhcMFgdKG3qgUsiwLiNqwnEXFSSgpsuCum4Lnvj0JLatjJ3QUffGDWlo6bPhkxO9c4pltHLKPafBg8kpEZGEuTxeVHWYkboAd31VChm0IQp26yXJaTBY4fGKWJmgC3QoRHQGOYnD/58e7zTj44YerM+ImnTlz0X58QCAbz53FD1WJ76yJXOSYxIQOY/GSK39NoSHKhARppzT62nhMTklIpKwV4+0o8tsxw0laQtyvSiNEgNc1ksSM9o0hct6iaQvd+QmUml9D2q6LDh7ecykx6VEqVGYHIHqTjNyEsJx9nL9hGNClXJcvSYFu6q65tQYqa1/iGNkggyTUyIiifJ4RTz0wQnkJ+lw7srYBblmlFqFPi7rJYmp7TJDpZAhQ88vmURSF6FWIikiFM8fbAWACftNTzVaPb19SyYEQZj0mBtKUuH2inipbPaNkVr7bNxvGmSYnBIRSdSbFZ1o6hnE17dlTflD29ei1CqOkiHJqemyYEWcFgo5v7YQBYPcRB0sDjd0oQoUJEdMedzNGzNw36W5uGJV0pTHZMWFo2SkMdKpc1HPRBTF4cop95sGFX7KExFJkNcr4k/vNyArTouL8hMW7LpRaiW79ZKk2F0eHDrZj7XpExuqEJE05SQOL8E/e3kM5LKpb65GqJW4fWsmlGe48fS5Vclo7rWhudc24xh6B50YcnlYOQ0yTE6JiCTo3ePdqO224O5tyyGb5ge7r0WqVezWS5JSWt+DIZcH2/PiAx0KEc1Q7khTpE0rpl7SOxtFKcPV14p204xfMzpGhntOgwuTUyIiiRFFEX/e04C0aDUuL5p6qZM/RGtUsDjccHm8C3pdoqm8U92N8BAFNiyb2CyFiKRpa3YsbihJw47CRJ+cLzs+HCq5DJUdM09OR8fIpESzchpMmJwSEUnMR/U9KG8z4WvnLl/wPXZR6uF2++zYS1Lg8Yp4r6Yb5+bEQaXgVxaiYKELVeKXVxUiSqPyyflUChlWJoSjcjaV035WToMRP+mJiCTmT3sakKALxVVrkhf82pHq4S8SnHVKUnC0tR89VieX9BIRCpIjUNlunnFTpLb+IURrVNCEKPwcGfkSk1MiIgk50NSHA019uPOcTIQoJg4t97fokbvc3HdKUrC7uhtKubBgo5SISLoKknUwDbnGluueCcfIBCcmp0REEvJYaRP0GhWuX58WkOtHjizrZcdekoJ3qruxMVMPXagy0KEQUYAVjoykmenS3vb+IS7pDUJMTomIJKSxx4p1GVEIUy181RQYnnMKcFlvMOobdOJbzx+FwWIPdCg+ccJoRaNxkEt6iQjAcFMkhUyYUcder3d4xikrp8GHySkRkYQYLQ7EhocE7PpMToPX0/ua8cqRdrx4qC3QofjEO9XdAIALcpmcEhEQqpQjOz4clR3mMx5rtDrg9HiREs3KabBhckpEJBFOtxf9NhfiwkMDFkOYSo5QpYzdeoOMxyviuYOtAICdxzoDHI1v7K7qQkGyDkmRrHwQ0bCCZB0q201nbIo0OuOUldPgw+SUiEgieqwOAAho5RQYrp72sSFSUPmo3oj2gSGUZESjutOMRqM10CHNi9HiwJHWAWzPTQh0KEQkIYXJEegbdKLTNP32hdGmSdxzGnyYnBIRSYTRMpKcagOfnA5wWW9QeWZ/C/QaFR64thhA8FdP3zveDVEELsznkl4i+kz+SFOkM+07ZeU0eDE5JSKSCMNIchqnC3ByqlGyW28AdZqG4PXObI4fAHSb7XivxoBr1qUgNVqN9RlR2FkR3MnpO9XdSIkKQ05CeKBDISIJyUvUQS4TUHWG5LStfwix4SEIVQamuSDNHZNTIiKJGKucBnhZb6RaxTmnAdJttmPrb/bgB/+unPFrXjzUCo9XxA0j44cuK0xETZcFDQbLpMc73B7sqTHA7fH6JGZfszndKG3owfa8eAiCEOhwiEhCQpVyZMVqz1w57eeM02DF5JSISCJGk1O9JrDJabRaxW69AfJ+jQEuj4in9rXg5bIzd931eEU8e6AVm7L0yIjRAAAuKUyEIAA7j3VN+poHdtfh1scP4pbHDoztcw6UfY29+ON79dh5rBO1XRY43B58WNcDh9vLETJENKmC5Igzduxt44zToKUIdABERDTMYLEjWqOCShHY+4ZRaiUGhlzweEXIZaxcLaT3jhuQHBmG1OgwfP+VCuQm6pCbqJvy+NFGSN+7NGfssXhdKNZnROONYx34xgUrxh3fYLDisdImrE6LxOHmflz+x1L85T/WYlVqpN/e01SGnB58/Zkj4xJkuUxAmFKOiDAlSjKiFzwmIpK+gmQdXiprQ7fZjnjdxO72Hq+IjoEh7ChKDEB0NF+snBIRSYTR4gh4MyRgeFmvKALmIe47XUh2lwcfN/Tg/Nw4/OGG1dCFKvG1pw7DbJ/67+HZA8ONkC7MG9/VdkdRIuoNVtR1f7a0VxRF/Pj1KoSp5PjbLevw0tfOhlwm4Nq/fopn9rdMOZrB5fHieKcZ/zrchp+8Xo2fvF4NyzQxzdST+06ix+rAE7eVYOc9m/Hg9atw97nLsTU7Bt+5MBsKOb+iENFEhSNNkSqnWNrbZbbD7RWRyhmnQYmVUyIiiTBaHQHfbwoA0RoVAKDf5kTUyL+T/33a2Ishlwfn5cQhLjwUf75pDW54ZB++80I5Hr557YT9lwazHe8eN+Arm5dNqLZfXJCAH/27Cm8c68S924ebCu2q6sZH9T344eV5iNGGIEYbgjf+czO+8dxRfP+VCuytMyAxIgyDDjcGnW4MOjzosTpQ322Fc2R/aqhSBpdHRGmDEY9+cf2cv/xZHW785YMT2Jodi63ZsQCA/KSIOZ2LiJaW3EQdBGG4Y+/5uROX/7NTb3DjbUkiIokwmB2Ik0ByGqlWAgD3nS6w948bEKaUY2OmHgCwPiMa37s0F7uru/HIh40Tjn9hpBHS9SVpE56LCw/FhmV67DzWAVEUYXd58LOd1VgZH46bN6aPHRepVuGxL63HPeevwMcNvXj1aDs+buhBXbcVAzYn9NoQ3LopAw9evwrv3rsVVT++GE/cVoIukx1X/vljHDrZN6f3+o/SJvTbXPj29uw5vZ6Ili5NiALLY7WobJ983ylnnAY3Vk6JiCRAFEXJVE6j1COV00Eu610ooiji/RoDNmXFjBt9cNumDJQ19+PXb9dgb50RseEhiAsPQWx4CJ490Iqzl+uxbKQR0ukuK0rE/7xaidpuC96u7EJb/xCeu2PjhOWycpmAe7dn494ZJoqbsmLwyt2b8OXHD+LGv+3Hr64uxFVrUmb8Xk02Fx75qBEX5MajOAB7XYko+BUk6bCvcfKbY619NggCkBTJymkwYuWUiEgCzENuON1eSSSnpy7rpYVR121F+8AQzs+NG/e4IAj49TVFuHZdKhxuL460DODJfc34xZs1aB8Ywi1npU9xxuGlvTIBeHhvI/7ywQnsKEocq8rO1/JYLV65axPWpEfi3hfK8bvdtTN+7d9LG2Gxu2ecDBMRna4gOQJdZvtYl/tTtfbbkKALDXhzQZobVk6JiCTAaLUDCPyMU4DLegPhvZpuAMC2lXETntOGKPCrq4vGfi+KIgadHljsLiRGTF0ZiNGG4KzlerxypB1hSjnuuyzXpzFHaVR44rYNuO+VCvzh/QbER4Tipg1TJ8sA0Gt14LHSJlxWlIi8pKm7EBMRTadgtClSh2nC5ybHyAQ33lIgIpIAw8jdXykkp9oQBRQyAf22My/rHXS4cd8rFegN8LzMYPf+cQMKknVIiJg4FuF0giBAG6KYNjEddVlhEgDg6+dlzej42VIpZPjV1UU4d2UsfvhaFQ6eYQ/qwx82YsjlwbdOG3FDRDQboze3qibp2NvWZ2MzpCDm9+RUEISTgiBUCIJwVBCEQ/6+HhFRMBpdmiSFhkiCICBKo8LADCqnpQ09eHp/C96s6FyAyBan/kEnylr6cV7OxK6T83X12mT89gvFuH1Lps/PPUouE/Dg9auRGq3G1546jI6BoUmPM5jt+OcnJ/G51cnIigv3WzxEtPjpQpVYFqNBxWnJqdPtRZfZjhSOkQlaC1U53SaK4ipRFNct0PWIiIKKcaxyeubK2UKIUivRN3jm5LS6Y7hb4uHmfn+HtGjtrTPCKwLn50xc0jtfIQo5rlmb4ve9VxFhSvztlrWwu7y448lDsLs8454/0tKPu54ug8cr4hvns2pKRPOXn6RDeatp3NzlTtMQvCLHyAQzLuslIpIAo8UBlUIGXag0WgFEqlUzWtZbNZqctjA5nav3agyI0YaMDZYPVllx4fi/61ahqsOM7750DKIoorLdhNseP4jPP/QJGnsG8curCpGun7y7MBHRbFyYn4Ausx1bfrMHf917Ajanm2NkFoGF+BYkAtgtCIII4GFRFB9ZgGsSEQUVg2V4xqkgCIEOBQAQrVahscd6xuOqO0yQywS09g3BYLYjTieNym+wcHm82FtrwEX5CZDJpPF3Px8X5MXj3guy8cA7dWjsGcSxNhMiwpT4r4tW4ktnZ0ATIo2bL0QU/K4oTsIyvQYPvFOLX71Vg79/1IRVqcM3+Vg5DV4LUTndJIriGgCXALhbEIStpz4pCMIdgiAcEgThkNFoXIBwiIikx2iRxozTUVEaJfrOMOe0f9CJDpMd23OH90pyae/sHW7uh9nunjBCJph9/bws7ChKRJNxEN+8YAU++n/bcPe2LCamRORzhSkRePzWErz41bOwPFaDd48boJAJSJxBczmSJr//pBBFsWPknwZBEF4BUALgw1OefwTAIwCwbt060d/xEBFJkdHiQLpeOsuQItXDDZFEUZyymlvdObyk97r1qXi/1oDDzf24pDBxIcMMeu/XGKCUC9i8IjbQofiMIAj44w2r4fKInDNIRAtifUY0nrtjIz450QuL3QWFnJ89wcqvf3OCIGgEQQgf/XcAFwKo9Oc1iYiCkcFiR5xOOpXTaLUKbq8Iq8M95TFVHcNdEotTI1GcEoFDrJzO2nvHu7ExUw/tIqsqCoLAxJSIFpQgCNiUFYOLC3iTNJj5+ydHPIBSQRDKARwAsFMUxbf9fE0ioqDidHvRb3MhViudZUiRaiUAoH+apb1VHWYkRoQiWqPCmvQoVHWYJnRppanVdVtwwjjoly69REREwcivyakoio2iKBaP/MoXRfHn/rweEVEw6h0cHSMjocqpRgUA6J9m1ml1hxn5I4PQ16ZFweURJ8yco6m9VNYGhUzAjuKkQIdCREQkCVxzQ0QUYAbzcHIaJ6HkNFI9fXI65PTghNGKvKThzohr06MAAIdOcmnvTHi8Il490o5zV8YiRiudv3ciIqJAYnJKRBRgRov0KqdRI8t6+wYnT05ruszwihirnOq1IVgWo2HH3hn65EQPus0OXLUmJdChEBERSQaTUyKiADNIMDlNjgqDNkSBA019kz5f1THcqTcvUTf22Jq0KJS19EMU2Xj9TF4ua4cuVIHzuN+UiIhoDJNTIqIAG62cSml5Z4hCjvNz47Crqgtuj3fC89WdZkSEKccNOl+XEYW+QSeaegYXMtSgY3W48XZlF3YUJyFUKQ90OERERJLB5JSIKMCMVjui1ErJjd64pCAR/TYX9k9SPa3qMCMvUTduBurovlMu7Z3e25VdGHJ5cNXq5ECHQkREJCnS+iZERLQEGcwOSS3pHXXuylioVXK8WdE57nG3x4uaTjPyknTjHs+K1UIXqkBZC5PT6bxc1oa0aPVYMk9ERETDmJwSEQWY0epAXLh0ZpyOClXKsS1neGmvx/vZPtKmnkE43N6xZkijZDIBa9Kj2LF3Gh0DQ/i0sRdXrUkeV3UmIiIiJqdERAFntEizcgoAlxYkosfqxMGTny3tHW2GlD8yRuZUa9OiUG+wwmRzLViMweTVo+0QReCq1ezSS0REdDomp0REASSKIgwSTk7PXRmLUKUMb52ytLeqwwSVQobMWM2E40eXqpa1snp6OlEU8XJZO9ZnRCFNrw50OERERJLD5JSIKIDMdjecbi/iJJqcakIUODc7Dm9VdsE7srS3qsOMnIRwKOUTf4QUp0ZCLhNQxqZIE1S0m9BgsHK2KRER0RSYnBIRBZBRgjNOT3dJYQIMFsfYDNPqTvOE/aajNCEK5CaGc9/pJF4ua4dKIcOlhYmBDoWIiEiSmJwSEQWQwWIHAMRKaMbp6c7LiYNKLsObFV3oMNkxYHMhb5L9pqPWpkXhaOvApPNRlyqTzYVXj7Zje248IsKUgQ6HiIhIkpicEhEF0GjlNE4n3eQ0PFSJrdkxeLuyE5XtJgBAXuLklVMAWJsRjSGXB+/VGHwWg/eUbsHB6Kc7q2Gxu/G1c5cHOhQiIiLJYnK6yJnt7JhJJGVjy3q10hslc6pLChLRYbLjuQMtEAQgNzF8ymMvyI1DTkI4vvX8UVS0meZ97X8dbkPJL96DaSg4P8/21hnxr8Nt+Oo5mShInrriTEREtNQxOV3EPmnowaof78auqq5Ah0JEUzBaHFApZNCFKQIdyrQuyI2HUi5gT60RmTEaqFVTx6tWKfDP20oQpVbh1scPoLl3cF7X/qDWgB6rA68eaZ/2OLvLg26zfV7X8jWrw43vv1yBrDgt/vO8FYEOh4iISNKYnC5ie2oN8IrAd14sR0uvLdDhENEkjBYHYrUhEAQh0KFMK0KtxKasGACYdr/pqHhdKP55WwncXhFffOwAeq2OOV+7vG0AAPDM/haI4tTLe7//SgUu+N1e9A0653wtX/v1WzXoMA3h11cXIVQpD3Q4REREksbkdBHb39SHrDgtBAB3PXMYdpcn0CER0WmkPOP0dJcWDHeZnapT7+my4rR49Ivr0WW247bHD8LmdM/6mr1WB1r7hrAyPhy13RYcnmJETUuvDa8d7YDF7sbDe0/M+jr+sL+xF0/ua8atZy8bm/9KREREU2NyukhZHW5UtptwSUECfvuFYlS2m/HznccDHRYRncZocUh2xunpLi5MwPa8eFyUnzDj16xNj8Ifb1iDinYT7n66DJ5ZNjYarZp+99IchIco8Mz+lkmPe/jDE5ALArZmx+Kfn56EIcDLe4ecHvy/l44hLVqN71yUHdBYiIiIggWT00Xq0Mk+eEVgwzI9LsxPwO1bluHJfc14vbxjzucURXHWXyyJaHpGa/BUTnWhSvztlnVYFqOZ1eu258XjvsvysKfWiLKW2c0/PdpqgkwASjKi8bnVyXijohMDtvHLdg0WO1483Iar1ybjp1fmw+UR8ec9DbO6jq/9/t06nOy14VdXF067P5eIiIg+w+R0kTrQ1AeFTMCa9EgAwH9fnIO16VH47kvH0Gi0zugcZrsLH9Ub8cf36nHb4wex9mfvovjHu/F/79bB6pj98jwiGs/p9qJv0Bk0yel8XF40vCR4dBTNTJW3DiA7PhyaEAVu3JAGp9uLl8rGN0Z6tLQJbo8Xd25djnS9BteuS8EzB1rQ1h+Yvfa1XRY8WtqEG0pScfbymIDEQEREFIyYnC5S+5v6UJgSMXbHXimX4U83roZKIcNdT5dh8AzJ5SMfnsCqH+/GzY8ewAPv1KGlz4bzc+KwKUuP/3u3Hlt/swePlTbB4eY+VqK56h0cmXEaLu0xMr4QGx6CGK0K1R3mGb9GFEWUtw2gOGX4Jltuog6r0yLxzP7mscZIJpsLT33ajMuKkpAxUtH9z/NWQICAP71/5uqp0eLAcwda8OXHD+LnO6vn8M4mxvyTN6qgDVHgvy/Kmff5iIiIlhKuNVqEhpweHGsbwJc3Z457PDEiDA9evxq3Pn4Qdz55GI9+aR1CFBO7R/67vAO/eLMGF+TG44tnp6MoJRIRYcqx58tbB3D/rlr85I1qPFrahP/dkYeLC2a+B42Iho3NOF0ClVNBEJCXFIGqWSSnLX02DNhcKE6NHHvsxpI0/Ne/jmF/Ux82ZurxxKcnMej04GvnLB87JikyDDduSMOT+5px5znLJyxD7jLZ8e/yduyu6sbhln6IIhCpVuK9GgOKUiJxeXHSnN/n7upufNzQix9fkY8ojWrO5yEiIlqKWDldhI609MPlEbEhM3rCc1uzY/Hrq4tQ2tCDbz53dMIe0oMn+/CdF8pRkhGNP9+0GltWxI5LTAGgODUST31lA57+ygaEhypwz3NH4HR7/fqeiBYjg3npJKfAcJffeoNlxp8XR1uHmyEVp342umZHURJ0ocONkWxONx77uAnn5cQh77QOwndtWw6VXIYH360be6xv0ImfvVGNrffvwS/erMGQy4Nvnp+Nt76xBYfuuwCrUiPxv69VznlWqt3lwc93Hkd2vBY3bUib0zmIiIiWMiani9C+pj7IBGDdFKMLrlmbgv+5LBdvVXbh+y9XjC2PazRacfsTh5ASFYaHb147aVX1VJuyYvD187LgdHtR123x+fsgWuyM1tFlvUsjOc1L1MHlEVFvmNnnxdHWAYQqZVgZHz72WJhKjqvWpODtyi785YMT6Le5cNe5yye8Ni48FF88OwOvlXegrKUfD45uR/i4CVcUJ2Hvf52LnfdswTcuWIHcRB0Uchl+d20x7K7hLrvTzVOdymMfN6Glz4Yf7MiHQs4fr0RERLPFn56L0P7GXuQnRSA8VDnlMV/Zkomvb8vC84da8au3a9BrdeDWxw9CJgj4x63rZ7wcrTB5uKJRMcsmJ0T02bJevXZpLP8cnY8606W95a0DKEyOmJDo3bQhDU6PF398vwElGdFYlzFxlQgAfPWcTGhVClz10Cf4/bt12JwVg13f3IrffqEY6fqJHYczY7X43iW5+KDWiGcPtM7qvXWb7fjT+w3YnhePzSvYBImIiGgumJwuMg63B0daB7Bh2eRf1k717QuzcdOGNDy8txGX/aEUnSY7/nbLukm/tE0lLVoNXagCx9qYnBLNlsFiR6RaecZVCotFhl4DtUo+o6ZILo8XlR3msWZIp1oRH471GcMrQ+7aNrFqOipSrcJ9l+Vie148Xr17E/5681qsOKUKO5mbN6Zjc1YMfrazGs29g2eMc9Sv366B2yPify7LnfFriIiIaDwmp4tMeasJTrcXJTNITgVBwE+uLMDlxUnoMtvx+2tXYe0US4GnO0dBcsSsx0MQEdBlciyZJb0AIJMJyE3UzSg5re0a3pt6ajOkU/2/i3Nw59ZMnJMdO+15ri9Jw99uWYdVU5xnshh/c00R5DIB336hfEaznY+09OPlsnZ8ecuyWd3cIyIiovGYnAbQR/VGmIZcPj3n/sZeCAJmlJwCgFwm4MHrVuGT756Hy0bmEM5WYXLE2BdJIpoZr1dEWUs/CpIiznzwIpKfpEN1pxneMyR9o82Qpkoq12VE43uX5kIQBJ/HmBQZhp9cmY9Dzf24f1fttAlqo9GK//7XMcSGh+DubVk+j4WIiGgpYXIaIB839ODmRw/gHx83+fS8B072YWV8OCLVM9/DJpMJSIoMm/M1C1Mi4PSwKRLRbFR3mtE36Fxy+xPzk3SwOtxo6bNNe1x56wD0GhVSoub+2TQfn1uVjGvWpuCve0/gqr98gpqu8dVeURTx5L5mXPqHj2CwOPC7a4uhDeF0NiIiovlgchppMpnqAAAgAElEQVQAbo8XP369CgBwpGXAZ+d1ebw43Nw/o/2mvsSmSESz91F9DwBgc9bSSk7zEoc/L6o7p1/ae7R1AMWpkX6pjM6EIAi4/5oiPHj9KrT22bDjD6V4YHct7C4PDGY7bn38IP731Uqsz4jG7m9txZYV0y8vJiIiojPjbd4AeGpfM+q6rUjXq1HeNgBRFH3yBayi3QSb04MNmXofRDlzo02RKtpNuGFBr0wUvEobjFgZH444XWigQ1lQ2QlaKGQCqjpMuLRw8q0EFrsLDUYrdhQlLXB04wmCgCtXJWPLilj8bGc1/vh+A3Ye60S/zQmb04OfXJmPmzemByyBJiIiWmxYOV1gfYNO/O6d4ZEGd2zNxIDNdcblbTN1oKkPwMz3m/oKmyIRzY7d5cHBk/1LbkkvAIQo5MiK0047Tqai3QRRBIpTpbEfN1qjwu+uXYV/3lYCl9eL1Gg1dt6zBbeclcHElIiIyIdYOZ2nf5d3IEOvRtEk4w4m88DuWgw6PfjB5XlweYYbCB1tHfBJh8f9jb1YHqtBjHbhu38WJkfgHx+fhNPthUrBex5E0znQ1Aen27skk1MAyEvSoXRkWfNkyluHb3RNNkYmkM7JjsXe72yDIIBJKRERkR8wi5gHt8eL/3qxHL98s2ZGx1d3mPHsgRbcvDEd2fHhyI4PR6hSNvZFbD48XhGHTvYv+JLeUQXJbIpENFOlDT1QyWULvj9cKvKTImCwOGC0OCZ9vrx1AOl6NaI0M2/stlBkMoGJKRERkZ8wOZ2HeoMVDrcXB072oX/QOe2xoijiR69XISJMiW9dkA0AUMplKEiKQHnb/JsivXGsAxaHO2BfdotS2BSJaKY+qu/BmvRIqFVLc/FKfpIOAFDVMfnnRXnbwIznkhIREdHiweR0Hirahr9Yebwi3q8xTHvszopOHGjqw7cvXIkItXLs8eLUSFS2m8aW+M6WKIr4+0eN+ObzR7EqNRLb8+LndJ75OrUpEhFNzWhx4HineUl3d80bSU4n69jbbbaj02SX3JJeIiIi8j8mp/NwrH0A4SEKJEaEYldV15THuTxe/PLNGuQm6nBDSdq454pTI+Fwe1HbNfvlsB6viB+/Xo2f7TyOi/MT8NwdGwNWiWFTJKKZ+eTE0hwhcypdqBKp0WGTNkUqa+4HMPzZSEREREsLk9N5qGgzoSA5AhfmxePDeiOGnJ5Jj3unuhvtA0P49vZsyGXj9yqtGqkOzHZpr83pxp1PHsLjn5zEHVsz8ecb1yBUKZ/bG/GRwuQI1HRa4HTPrQpMtBR8VN+DiDAlCpKl0Yk2UPITI1B9WnJqd3nwwDt1SNCFoiBZF6DIiIiIKFCYnM6R0+3F8U4LilIicGF+AuwuLz6qN0567NP7m5EcGYZtOXETnkuNDkOUWony1pknp4MON657eB/erzHgp1fm4/uX5kImC3yDDjZFIpqeKIoore/Bpiz9hBtVS01+kg4newdhdbjHHntgdy0aDFb85poihCgCe7ONiIiIFh6T0zmq67bA6fGiMCUCJcuioQtVYHd194TjGo1WfNzQixtKUif9MioIAopTI2fVsffFQ62oaDfhoZvW4OazMubzNnyqMJlNkYimc8JoRZfZjs1ZS3e/6ai8JB1EEagZ2Xe6v7EXfy9twk0b0rA1m38+RERESxGT0zk6NtIMqSg5Ekq5DOfnxuO9491wn9bY6Jn9LVDIBFy7PnXKcxWnRKLOYBlXQZiKKIp4an8LilMicHFB4vzehI+l69UIn6IpUllLP/acoWkU0WL30chszy1LdL7pqfKThm9mVXWYYXW48Z1/lSM1So3vX5ob4MiIiIgoUJiczlFF+wAiwoabegDAhXnx6Le5cGikmQcwvH/qX2VtuCg/AXHhoVOea1VqJEQRM2omtL+pDw0GK27amD7/N+FjgiCgcJKmSBVtJtz4t324+5myKfflEi0FpfU9SNerkRqtDnQoARevC4Feo0J1hxm/ePM42vqH8MC1xdCELM3xOkRERMTkdM6OtZlQlBIxNox9a3YsVArZuK69b1Z0YsDmwk0b0qY6DYDPZoTOZN/pU/uaoQtV4PKipHlE7z+nN0XqMtnxlScOQiGTweb0YE8tq6e0NLk8Xuxr7F3SXXpPJQgC8pJ0eLuqC8/sb8HtWzKxPiMwc5qJiIhIGpiczoHd5UFtl2VsjyUAaEIU2JIVg91V3RBFEcBwIpkZo8FZy/XTnk+vDUFqdNgZO/YaLQ7squrCNWtTEaaSZrOQU5si2ZxufOWJg7Da3Xj+zo2I0Ybg9fKOQIdIFBBHWgYw6PRwSe8p8pJ0MA25kB2vxb3bswMdDhEREQUYk9M5qOmywO0Vxyqeoy7KT0D7wBCqO82o7jCjrGUAN25IG6uuTqc45cxNkV441AqXR8RNG6evxAbSaMJ+rM2Ee58vR3WHGX+8cTXykyJwWWEC3q8xzGhvLdFiU1pvhEwAzlrO5HTU2ctjoFHJ8cAXVgV8FBYREREFHpPTOagYqXAWpowfEn9+bhxkArC7qhtP729GiEKGa9amzOicq1Ij0T4wBIPFPunzHq+IZ/a34OzleiyP1c7vDfjRaFOk+3fV4O2qLtx3WR7Oy4kHAOwoToLD7cW7k3Q1Jlrs9tYZUZwaiYgwZaBDkYxzsmNR/sMLUZiytGe+EhER0TAmp3NwrM0EvUaFpIjxTY702hCsS4/G68c68OqRduwoSkKkWjWjcxanDie6x6aonn5Qa0D7wBBulmAjpFONNkXqt7lwQ0kabtuUMfbc2rQoJEaE4o1jXNpLS4vR4kB5mwnnrZw463ipU8j5Y4iIiIiG8VvBHFS0m1B4SjOkU12YH49G4yAGnZ5ZLb/NT9JBLhOm3Hf61L5mxIWH4IK8+DnHvVCuW5+KL6xNwU+uzB/3ZySTCbisMBF764ww2VwBjJBoYe2tMwIAtuUwOSUiIiKaCpPTWRpyelBvsKIoefJlaNtHkse8RB1Wp0ZOesxk1CoFsuPDcXSSjr2tfTZ8UGfE9SVpUAZBleHKVcm4/wvFk8Z6eXESXB4Ru6q7Jnkl0eK0p8aAuPAQ5CfpAh0KERERkWRJP9ORmOpOMzxeccJ+01Hpeg3uOnc5vn9p7owaIZ1qVWoEylsHxrr9jnrmQAtkgoAbSlLnHLdUFKVEIC1aza69tGS4PF58WG/EtpVxs/5MICIiIlpKOO18lkabIZ3eqfdU/31xzpzOXZwSiWcPtOJo6wAUMhla+21o67fh+YOtOD8nDokRYXM6r5QIgoAdRYl4+MNG9Fod0GtDAh0SkV8dbu6Hxe7GtpzYQIdCREREJGlMTmfpWLsJceEhiNeFnvngWRptivT5hz4Z93iMNgR3b8vy+fUC5fLiJDz0wQm8VdmF/5B4gyei+dpTY4BSLmDzCianRERERNNhcjpLFW2maaum85GTEI4f7MiDCCAlKmzkl3rRjZ7ISQjH8lgN3jjWMS45dbq92FnRgdQoNdZlRAcwQiLf2VNrQMmyaGhD+HFLRERENB1+W5qFQYcbDUYrdhQl+eX8giDgts3L/HJuKREEAZcXJ+HB9+rRbbYjSq3CS2Vt+NP7DWgfGEJ+kg4779kS6DCJ5q2t34a6biuuXRf8+8WJiIiI/M3vDZEEQbhYEIRaQRAaBEH4rr+v509VHWaI4vT7TWlmdhQlQRSBH7xWiW2//QDfe7kCMVoVzsmORX23FS6PN9AhEs3bnlqOkCEiIiKaKb8mp4IgyAH8GcAlAPIA3CAIQp4/r+lPx0aaIRVMMUaGZi4rTovcRB12VXUjNjwEj9+6Hq/evQlXrUmG0+NFo3Ew0CESzdueGgPSotXIjNEEOhQiIiIiyfP3st4SAA2iKDYCgCAIzwG4EkC1n6/rFxXtJiRGhCI2nB1mfeFPN66G0eLAhmXRYyM2chOH50BWd5qwMiE8kOERzYvd5cEnJ3pw/fo0jpAhIiIimgF/L+tNBtB6yu/bRh4LShVtJhSyauozy2O12JipH/fFPTNGA5VChuOdlgBGRjR/nzb2wu7yckkvERER0Qz5u3I6WblAHHeAINwB4A4ASEtL83M48/PLqwqhUvh9m+6SppDLkB2vxfFOc6BDIZqXPTUGhCnl2LCMnaeJiIiIZsLfmVYbgFPbVKYA6Dj1AFEUHxFFcZ0oiutiY6U9B3BDph6r06ICHcail5ugY3JKQU0URbxfY8CmLD1ClfJAh0NEREQUFPydnB4EsEIQhGWCIKgAXA/g336+JgW53EQdeqxOGCz2QIdCNCcnjFa09Q9xSS8RERHRLPg1ORVF0Q3g6wB2ATgO4AVRFKv8eU0KfnlJw02RuO+UgtWemuERMueuZHJKRERENFP+3nMKURTfBPCmv69Di0duwkjH3g4zzsmW9lJvoskcau7DshgNkiPDAh0KERERUdBgdx+SnAi1EsmRYdx3SkGrpsuCvJGxSEREREQ0M0xOSZJyE8OZnFJQGnS40dxrQw7n9BIRERHNCpNTkqTcRB0aewZhd3kCHQrRrNR2D++VzmHllIiIiGhWmJySJOUm6uDxiqjvtgY6FKJZqRlp5MXKKREREdHsMDklSRrdr1fdaQpwJESzU9tlhjZEwWZIRERERLPE5JQkKS1aDY1KznEyFHSOd1mwMiEcMpkQ6FCIiIiIggqTU5IkmUzAyoRwVLMpEgURURRR02nmkl4iIiKiOWBySpKVm6jD8U4zRFEMdChEM9JpssNsd7MZEhEREdEcMDklycpN1MFid6N9YCjQoRDNSE3XcKU/l5VTIiIiolljckqSlTtSfeK+UwoWo/+tZjM5JSIiIpo1JqckWTkJ4RAEoLqD+04pONR2WZAcGQZdqDLQoRAREREFHSanJFmaEAUy9BocZ1MkChI1XWbkJrJqSkRERDQXTE5J0nITw3G8i8kpSZ/D7cEJ4yByEtgMiYiIiGgumJySpOUm6NDca4PV4Q50KETTajBY4fGKyGHllIiIiGhOmJySpI02Rapl9ZQkrmakGRIrp0RERERzw+SUJC03afiLPpsikdTVdJmhUsiQoVcHOhQiIiKioMTklCQtKSIUEWFKVHOcDElcTZcF2fFaKOT8WCUiIiKaC36LIkkTBAHZ8VqcMFoDHQrRtGq6LFzSS0RERDQPTE5J8tL1GjT3DgY6DKIp9VgdMFocyElgMyQiIiKiuWJySpKXoVej2+zAkNMT6FCIJlXbNbzsfLSBFxERERHNHpNTkrx0vQYA0NJnC3AkRJM73jncsIuVUyIiIqK5Y3JKkpc+0v30JJf2kkTVdFkQGx4CvTYk0KEQERERBS0mpyR56dHDlVPuOyWpqu2ysGpKRERENE9MTknyItRKRKmVaO7lsl6SHrfHi7puJqdERERE88XklIJCml7D5JQk6WSvDQ63l2NkiIiIiOaJySkFhQy9mntOSZJqukaaISWyckpEREQ0H0xOKSik6zXoGBiC0+0NdChEAACvV8S71d14aM8JKGQCsuK0gQ6JiIiIKKgpAh0A0UykR6vhFYG2fhsyY5kEkG95vCLqDRYkRYZBF6qc9li7y4OXy9rx99JGNBoHkRwZhvu/UIQQhXyBoiUiIiJanJicUlDIiBkeJ9Pcy+SUfO+VI+34zovlAIAEXShWxGuxIi4cSZGhsDrcGLC5YBpyYcDmxLE2E3oHnShI1uEPN6zGpQUJUMi5CIWIiIhovpicUlBI1w+Pk+G+U/KHirYBaFRy3H1eFhq6ragzWPDMgWbYXcPLyMNDFYhUKxEZpsKGzGjcvDEDGzOjIQhCgCMnIiIiWjyYnFJQ0GtU0IYo2LGX/KK224KVCeG469ysscc8XhEWuwvaEAUro0REREQLgN+4KCgIgoC0aDWaWTklHxNFEbVdw8npqeQyAZFqFRNTIiIiogXCb10UNDJi1Kycks8ZrQ7021zIjucoGCIiIqJAYnJKQSNdr0Frvw0erxjoUGgRqeuyAgBWMjklIiIiCigmpxQ00qPVcHlEdAwMBToUWkRquy0AgOwEJqdEREREgcTklILGaMdeLu0lX6rrskCvUSFGGxLoUIiIiIiWNCanFDTGZp32sSkS+U5tt4X7TYmIiIgkgMkpBY348FCoFDJWTslnvF4R9d0TO/USERER0cJjckpBQyYTkB6txskeVk7JN9oHhjDo9LBySkRERCQBTE4pqKTrNWjpY+WUfKNupBnSygRtgCMhIiIiIianFFTS9Wqc7B2EKHKcDM3faKfeFaycEhEREQUck1MKKhl6NewuLwwWR6BDGWMw2wMdAs1RXZcFSRGh0IUqAx0KERER0ZLH5JSCitTGyRzvNKPkF+/hwzpjoEOhOajttnK+KREREZFEMDmloJIxkpye7JVGU6SqDjMA4N/lHQGOhGbL7fHihMGKlVzSS0RERCQJikAHQDQbSZGhUMgENE+SnIqiCEEQFjSeph4rAODd491webxQynm/x9dMQy5896VjaO61weZ0Y9Dpgc3hhlcEnvpKCdamR8/pvCd7bXB6vOzUS0RERCQR/CZNQUUhlyElKmzCsl6TzYULfrcXj3x4YkHjaRoZazNgc+FAU9+CXnupeGB3LXZVdSEpMhRFKZG4IDcO15ekQSET8NS+ljmf97NOvUxOiYiIiKSAlVMKOul6zbjkVBRFfP+VCpwwDqKi3bygsTQaB3H2cj3KWvqxq6oLm7JiFvT6i11luwlP7WvGLWdl4EdX5I97zub04NUj7fjp59zQhsz+o6y2ywJBALLiOEaGiIiISApYOaWgc/o4mRcOtWJnRSfkMgG91oXr4uv1imjqGUReog7nZMdiV1UXvF6OuPEVr1fE/7xaiWiNCt/anj3h+WvWJmPI5cGbFZ1zOn9dtwUZeg1ClfL5hkpEREREPsDklIJOul4Di92NfpsLDQYrfvTvapy9XI9tK+PQN+hcsDg6zXY43F5kxmpxcUECus0OHG0bWLDrL3YvHm7F0dYBfO+SXESETRz1siYtCstiNHjpcNuczl/bbUF2PKumRERERFLB5JSCToZeDQCo77bgnmePIFQpw++vW4XYcBV6rAuXnDYZh/ebLovR4LyceChkAnZVdi3Y9Rez/kEnfvVWDdZnROGqNcmTHiMIAq5anYz9TX1o7ZvdaCG7y4OTPYNYmaDzRbhERERE5ANMTinopI8kp997pQLVnWbcf00x4nWh0GtC0G9zLtjS2tFOvZmxGkSEKXF2Vgx2VXWNLTemubt/dy3Mdjd++rmCaTswf34kcX25rH1W528wWOEVwTEyRERERBLC5JSCTkqUGoIw3Izoi2el44K8eACAXquCxyvCNORakDgaewahVskRFx4CALg4PwEne22oHekCS3NT3jqAZw+04EtnZyDnDJXNlCg1zsrU4+UjbbO6KfBZp14u6yUiIiKSCnbrpaATqpQjPVqNUKUc37s0d+zxaI0KANA76EDUyL/7U6NxEMtiNGOVve158bjv1Qq8Xdl1xqSKhtV1W3DCYIXF7obZ7oLF7sabFZ2I1YbgmxesmNE5rl6bgu+8WI5Dzf1YnzGzmae13Rao5DKk6zXzCZ+IiIiIfMhvyakgCD8CcDsA48hD3xdF8U1/XY+Wln/eVgJdqHJcp9UY7XAFs8fqRFac/2No6hlEUUrE2O9jw0OwLj0Kb1d24ZsXTOwuS+N9WGfEF/9xAKcXPCPVStx/TTHCQyc2QZrMJQUJ+MFrlXi5rG3GyWldlwWZsRoo5Vw8QkRERCQV/q6c/l4Uxd/6+Rq0BE1W8dJrh6ulC9Gx1+H2oK3fhs+tShr3+EX5CfjZzuNo7h1kVW4arX023PPcEayMD8cD1xYjIkyJ8FAltCEKyGVT7zGdjCZEgYsLEvBGeSd+eHn+jEbD1HVbsS4jaq7hExEREZEfsGxAi8bYst4FmHXa2meDVwQyY8fvWbwoPwEAsKuKXXunYnd5cNfTZfB4Rfz1P9YiPykCKVFqRIQpZ52Yjrp6TQosDjd2V3ef8ViL3YX2gSFksxkSERERkaT4Ozn9uiAIxwRBeEwQBJYpyK+i1aN7Tv1fOW08ZYzMqVKj1chP0uFtjpSZlCiK+MFrlahoN+H3165CRoxvqstnZeqRFBE6o5mndd3DXZbZqZeIiIhIWuaVnAqC8K4gCJWT/LoSwF8ALAewCkAngAemOMcdgiAcEgThkNFonOwQohlRyGWIUivRuwCzTpt6hpPTyZKri/MTUNYygG6z3e9xBJvnDrbihUNt+M/zssa6LPuCTCbg82uS8VG98Yx/7vsaewEA+clsWkVEREQkJfNKTkVRvEAUxYJJfr0mimK3KIoeURS9AP4GoGSKczwiiuI6URTXxcbGziccIkRrVOgd9P+y3kbjIGK0KkSETWzac0nh8NJeVk/HO9o6gB++VoWt2bF+aRh19ZoUeEXgpbKpq6eiKOKlsjaUZEQjMSLM5zEQERER0dz5bVmvIAiJp/z28wAq/XUtolF6bciCVU5PX9I7KisuHNnxWuw81un3OIKFw+3B3U+XITY8BA9et2rOe0unkxmrRcmyaDx/sHXKmafH2kxoNA7iqjXJPr8+EREREc2PP/ec/kYQhApBEI4B2AbgW368FhEAQK9RLcye02mSUwC4tDARB5v7uLR3xOvlnWgfGMLPP1/g1xm0169PRXOvDfsa+yZ9/uWyNqgUMlxSmDjp80REREQUOH5LTkVRvFkUxUJRFItEUbxCFEWWkcjv9FqV37v1mu0u9FgdEzr1nuqywkSIIvBWBf+zF0URj5U2YUWcFudk+3fp/iUFiQgPVeCFQ60TnnO6vfh3eQe258VPuhybiIiIiAKLo2RoUdFrQjAw5ILb4/XbNU72TN6p91Qr4oeX9r5ZwX2n+xr7UN1pxm2bl0EQfL+c91RhKjk+tyoZb1Z0wmRzjXtub50R/TYXruaSXiIiIiJJYnJKi4peq4IoAv2nJSa+NNqpN/MMY1AuK0zi0l4Aj5Y2IVqjwudXL0xSeN36VDjcXrxW3j7u8ZfL2hCjVWHLCjZeIyIiIpIiJqe0qOg1IQDg1469jcZBCAKQpldPe9xlRQlLfmnvyZ5BvFfTjZs2pCFUKV+QaxYkR6AgWYdnD3zWGMlkc+G94wZcXpwEpZwfe0RERERSxG9ptKjotcPNdvr82LG3sWcQKVFhCFFMn2xlxYVjZXz4kl7a+/gnJ6GQCbh5Y/qCXve6dak43mlGZbsZAPBGRQecHi+uXpOyoHEQERER0cwxOaVFRT/SCbbHjx17m3qsWBYzdTOkUy3lrr2mIRdeONSKy4uSEKcLXdBrX7EqGSEKGZ472AIAeLmsHdnxWuQn6RY0DiIiIiKaOSantKjotcPLevv81LFXFEU0GQfPuN901FJe2vvCwVbYnB7ctnnZgl87IkyJywoT8e+jHTjeacbh5n5ctSbF7w2ZiIiIiGjumJzSohIZpoRMgN9mnRotDgw6PciMnVlyOrq0d+cSS07dHi8e/+QkSpZFoyA5IiAxXLc+FRaHG/c8ewSCAFy5KikgcRARERHRzDA5pUVFJhMQrVGhx097ThtnMEbmdJcWJuJQcz+6TEtnae/u6m60DwzhywGomo4qWRaNZTEa1Bus2LQ8BokRYQGLhYiIiIjOjMkpLTp6TQj6/NStt2kOyenY0t7KpVM9fay0CWnRalyQGx+wGARBwHXrUwEAV3G2KREREZHkMTmlRUevVaHXX5VToxUqhQxJs6jCfda113fJaWW7CU/ta4bb4/XZOX3FYLHjUHM/rl2XArkssHs8b96Yjv/dkYcdRVzSS0RERCR1TE5p0YnWqPy257SpZxDL9BrIZpl0jS7t/eVbx9FgsM75+qIo4un9zbjqoU/wP69W4sa/7UenaWjGr7c63HjlSBv21BrmHMOZfNzQAwDYmh3rt2vMlCZEgS9vXgaVgh91RERERFKnCHQARL4Wow1Br5+69Tb2DCI7LnzWr7vlrHRUdpjw94+a8PDeRqxOi8Q1a1NweXESdKHKGZ1jyOnBfa9W4OWydmzNjsXF+Qn42c5qXPrgR/jdtauwLSdu0tc53V58UGvAa+UdeLe6Gw63FyqFDO/dew5So9Wzfi9nUlrfi0i1EvlJgWmERERERETBickpLTp6jQpmuxvOkSTMV9weL1p6bbgoP2HWr43SqPC3W9bBYLHjtSMdePFwK+57pRK/fLMGz9y+AUUpkdO+/mTPIL761GHUdlvwjfNX4J7zV0AuE7AhMxp3P12GWx8/iDu3ZuI7F61Ej9WB6g4zqjvMON5lxscNvTANuRCtUeG69anYuiIW//nsEfzyreN46Ka1c/3jmJQoiihtMGLT8piAL+klIiIiouDC5JQWnWitCgDQN+hEQkSoz87bYLTC7RVn1QzpdHHhobh9aya+smUZKtpN+NpTZbj9iUN47e7NU8b6YZ0Rdz9TBpkg4LEvrce2lZ9VSJfHavHq3Zvw0zeq8fCHjXj8k5NwuD/bh5quV+P8nDhcvioJm7NioJQPJ+t3nbscD7xTh09P9OKs5fo5v5/TNRis6DY7sCkrxmfnJCIiIqKlgckpLTp6TQgAoHfQ4dPk9MlPm6FSyHDuyvnvpRQEAUUpkXj0S+tw9UOf4CtPHMSLd56NMJV83HGvl3fg3heOIisuHI/cvHbSZbihSjl+/vlCbFkRg48bepEdr0Vuog45iTpoQyb/X/z2rZl47mArfvx6FXbes8VnVc7Skf2mW1YwOSUiIiKi2WGXEFp0YkYqp77s2Gu0OPDi4TZcvSYFceG+S3hzEnT4ww2rUdVhxrdfPAqvVxx77un9zbjnuSNYnRqF5+/ceMb9oRcXJOKnnyvAzWdlYF1G9JSJKTCc0N53WS5quix47mCLz95PaX0P0vVqv+xlJSIiIqLFjckpLTrRmpHk1IezTp/49CRcHi9u37LMZ+ccdX5uPO67NBdvVgyYFPEAABKcSURBVHTh9+/WQRRF/HlPA+57pRLbVsbhn7eVzLhp0mxcUpCADcui8dtdtTDZXPM+n8vjxb7GXmzmkl4iIiIimgMmp7To6LUjy3p9VDkddLjxxKfNuCgvAZmxWp+c83Rf3rwM161LxR/fb8Ctjx/E/btqceWqJDx889oJS319RRAE/ODyPJiGXHjwvfp5n+9o6wAGnR4mp0REREQ0J0xOadHRhSqglAs+m3X6/MFWmIZcuPOcTJ+cbzKCIOCnnyvAhmXR+KDWiC+elY7fX7tqrIGRv+QnReD6kjQ88elJNBgs8zrXR/U9kAnA2cuZnBIRERHR7DE5pUVHEAREa1To80Hl1OXx4tHSJpQsi8bqtCgfRDc1lUKGv39xHZ78cgl+dEU+ZAs0iuXb27MRppLjgd118zpPab0RhSmRiFD7fgkyERERES1+TE5pUdJrQnyy53TnsU60Dwzhq36smp4qPFSJLStiIQgLNyNUrw3BjqIkfNzQA1EUz/yCSZjtLpS3mbA5y3djaYiIiIhoaWFySouSXqtCzzwrp6Io4q97TyA7Xotzs+PO/IIgtio1Ama7Gyd7bXN6/b4TvfB4RWzOmv+YHSIiIiJampic0qKk16jQN889px/W96Cmy4I7ti5fsCW2gVKcGgkAKG8dmNPrSxt6EKaUY016pC/DIiIiIqIlhMkpLUp6bQh6rZMv620wWHCyZ3DaJawWuwsP7WlAgi4UVxQn+StMyVgRFw61So6j80hOS5ZFI0Thn87CRERERLT4KQIdAJE/RGtUGHR6YHd5EKr8LGEasDlx6YOlcHq8iFIrUZwaiVWpkchPikCXaQhHW00obxvACaMVogj87448qBSL/x6OXCagIDkC5W2zT047BobQaBzEjSVpfoiMiIiIiJYKJqe0KMVoVQCA3kEnkiPDxh4vbeiB0+PFXecuR4/VgfJWE/bW1WO0iBqjVaE4JRKXFyVhTXrkkprZuSo1Eo9/chJOt3dWCXlpfQ8AYPOKpfNnRURERES+x+SUFiW9JgQA0Gt1jEtOP6wzQheqwL3bs6EYmSFqdbhR22VGQkQYkiJCF7RTrpQUp0TC6faitsuCwpSIGb+utKEHMdoQrIwP92N0RERERLTYLf71irQkRY9WTk/p2CuKIj6s68HmFTFjiSkAaEMUWJsejeTIsCWbmAJA0UhCenQWS3s9XhGlDT3YnKVf0n92RERERDR/TE5pUYoZrZye0rG33mBFl9mOrSs47mQyKVFh0GtUs+rYe7R1AH2DTmzLWdyjdoiIiIjI/5ic0qKkH6ucftaxd+//b+/eg+WsywOOf59cTjAXcgUKJNxqQIJjAkZRS2m5Sa2jouCIo1XbTinW3qbTaXVwOoxTpoXOtNMWW6W1pXQ6gmAZECsoCSNSuVTlGggkFCwhmBNAQhJuhjz9Y38HlsPu2bNn95x3z+73M/PO2X2vv91nn7Pv876/990HtwNw4pEWp41EBKtXLGqrOF2/cRszZ0Tf/w6sJEmSJp/FqfrS3KGZzJk14zVnTm/etJ2V+8/noLprUPVaq5cvYvP2Xex84Wfjmn/dA8OsPXQxC+fOnuSWSZIkqd9ZnKovRQTL5s955ZrT5196mdsfedqzpi2sXrGQTLj38R0t593y0+fY+JOdnHK0Z00lSZLUOYtT9a2l84d4anetW+/tjzzFS3v2Wpy2sHr5IgDu2dK6OL1p4zAApxx9wKS2SZIkSYPB4lR9a8m8IZ4u3XpvfuhJ5syawfGHL6m4Vb1t8bwhDl06d1zXna7bOMxhS+dyxLJ5U9AySZIk9TuLU/WtpfNe7db73YeGefvhS9hn9syKW9X7Vi9vfVOk517aw/cffoqT33SAPyEjSZKkrrA4Vd9aNn+IJ3e9yOPPPM/D23fzS3bpHZfVKxaxdccLDD/7QtN5btn0JC/t2ev1ppIkSeoai1P1rSXzhnhxz16+de8TABan47RmxUIA7h7jutP1G4dZMGcWbzvMbtKSJEnqDotT9a2l8+cAcPWdj3Pgwn144/7zK27R9HDMQQuZOSOadu3duzdZv3GYE4/cj6FZ/guRJElSd7hnqb61dP4QABu2PsuJK/fz2shx2mf2TI46YAF3b2lcnN63dQfDO1/k5DfZpVeSJEndY3GqvrV03tArj/0JmfasXlG7KdLevfm6aeseGCYCTrI4lSRJUhdZnKpvjXTrnRFwwhuXVdya6WXNioU8+8IeHn1q9+umrd84zHGHLGZJXfEvSZIkdcriVH1r5MzpmhWLWDh3dsWtmV5Wr1gE8LquvduefYF7H99hl15JkiR1ncWp+tY+s2eyevlCPnTc8qqbMu2s3H8Bc4dmct3dT/A/jz7NM8/Vfi92/cZhAE49+oAqmydJkqQ+NKvqBkiT6ZrfPaHqJkxLM2cEJ67cj+s3/IR1pSBdNn8OmcnBi97AkQd452NJkiR1l8WppIb+4WPHsXXH82wa3sWmbTvZtG0Xm7fv4ow1B3vnY0mSJHWdxamkhmbMCJYvnsvyxXM56SivMZUkSdLk8ppTSZIkSVLlLE4lSZIkSZWzOJUkSZIkVc7iVJIkSZJUOYtTSZIkSVLlLE4lSZIkSZWzOJUkSZIkVc7iVJIkSZJUuY6K04j4cERsiIi9EbF21LTPRcTmiHgwIk7vrJmSJEmSpH42q8Pl7wM+BHy5fmRErALOBo4BDgJujIgjM/PlDrcnSZIkSepDHZ05zcwHMvPBBpM+AFyemS9m5iPAZuDtnWxLkiRJktS/Juua04OBx+qebynjJEmSJEl6nZbdeiPiRuDnGkw6LzOvabZYg3HZZP3nAOcAHHLIIa2aI0mSJEnqQy2L08w8dQLr3QKsqHu+HNjaZP2XAJcArF27tmEBK0mSJEnqb5PVrfda4OyImBMRhwMrgTsmaVuSJEmSpGmu05+S+WBEbAHeCXwzIm4AyMwNwNeA+4Hrgc94p15JkiRJUjMd/ZRMZl4NXN1k2gXABZ2sX5IkSZI0GCarW68kSZIkSeNmcSpJkiRJqpzFqSRJkiSpchankiRJkqTKWZxKkiRJkipncSpJkiRJqlxkZtVteEVEbAd+XHU7WlgGPFl1IzRljPfgMNaDxXgPFuM9WIz34DDW09Ohmblfowk9VZxOBxHxg8xcW3U7NDWM9+Aw1oPFeA8W4z1YjPfgMNb9x269kiRJkqTKWZxKkiRJkipncdq+S6pugKaU8R4cxnqwGO/BYrwHi/EeHMa6z3jNqSRJkiSpcp45lSRJkiRVbtoXpxGxIiJuiogHImJDRPxBGb8kIr4TEZvK38Vl/NIy/66IuHjUuj4aEfdGxD0RcX1ELGuyzbeW+TZHxN9FRJTxJ0bEjyJiT0ScNUab50TEFWX52yPisDJ+TUTcWl7HPRHxke68S/2hx2L9NxFxVxkeiohnmizf9DMREZ8sbd4UEZ/sxnvUT7oc74+UWG+IiIvG2GanuT1WvK+PiGci4rpO3pd+1WPx7kZ+XxgR95XB/+V1JhDr0yLihyVWP4yIk+vW1TCGDbbZaW7/UUTcXz5X6yLi0Lpp5vYYeize483tc8vyd0XELRGxqm6a391j6HK8L4iIxyJiV4ttNot307wdtXzD/fIyzfyeapk5rQfgQOC48ngB8BCwCrgI+GwZ/1ngwvJ4HnACcC5wcd16ZgHDwLLy/CLg/CbbvAN4JxDAt4D3lPGHAW8BLgPOGqPNvwN8qTw+G7iiPD4SWFkeHwQ8ASyq+j3ulaGXYj1qnt8D/qXJ8g0/E8AS4H/L38Xl8eKq3+NeGroY76XA/wH7lef/BpzSTrzbyO2m8wGnAO8Drqv6ve3FoZfiPWqeieT3e4HvlP8184AfAPtW/R73yjCBWB8LHFQevxl4vJ0YjjVfG7l9EjC3PP405Xu7PDe3p0m8R80zVm7vW/f4/cD15bHf3VMb73eU9e1qsc1m+d00b0ct33C/vDw3v6d4mPZnTjPzicz8UXm8E3gAOBj4ALWdEsrfM8o8uzPzFuCFUauKMswrR1z2BbaO3l5EHEjtn9atWfvUXla37kcz8x5gb4tm17ftKuCUiIjMfCgzN5V1baVWQDX8gdpB1EuxHuWjwFebtLnZZ+J04DuZ+XRm/pTajuyvjPX6B00X430E8FBmbi/PbwTOHL29buT2WPNl5jpgZ8sXPqB6Kd6jTCS/VwHfzcw9mbkbuBvz+xUTiPWd5TsRYAOwTznTMa4Ydim3b8rM58rT24DlddPM7TH0UrxHGSu3n617Og8YuUGL390tdCveZdptmfnEWNtrkd9N83aUhvvlZR3m9xSb9sVpvXIa/ljgduCAkQ90+bv/WMtm5s+oHVW5l1qhsgr4SoNZDwa21D3fUsa142DgsbLdPcAOakf761/L24Eh4OE21z0QeiXWpYvI4cD6Nl/CK5+BZuvWqzqJN7AZeFNEHBYRs6h9aa1oMF83cltd0Cvx7iC/7wbeExFzo3bJwElN2jDwJhDrM4E7M/NFxp+z3c7t36R2dkZt6pV4jye3I+IzEfEwtTN+v1+3br+7x6nDeI/XeD8XY+Vty/1yTZ2+KU4jYj7wdeAPRx3xGu/ys6kVLMdS61J7D/C5RrM2GNfuLY/HXEc5CvTvwK9nZquzsAOnx2J9NnBVZr7cbjPGsW7RebzL0e1PA1cA3wMeBfY02lSjxdvdnjrTY/GeUH5n5reB/wK+T+3MzK1N2jDQ2o11RBwDXAj89sioBrM1ytmu5XZEfBxYC/zVRJYfZD0W75a5nZlfzMyfB/4U+HybbRh4XYj3uDfVYNxrYjKOvDWuPaQvitNSbHwd+I/M/M8yelsp8kaKveEWq1kDkJkPl24BXwPeFREz6y6e/wK1IzL13QKW06BL6Kj2XTCyjjJqC+UoejmyvxB4ujzfF/gm8PnMvG0cL3+g9GCsz6auW1CDWDfzymdgjHUPvC7Fm8z8RmYen5nvBB4ENk1SbqsDPRjvieY3mXlBZq7JzNOo7fhsarXMIGk31hGxHLga+ERmjvQoahjDycrtiDgVOA94f5tndgZeD8a7ndy+nFe7BfvdPQ5dinezdbcV70Z5285+uabetC9OS5/wrwAPZOZf1026Fhi5i9ongWtarOpxYFVEjFzjeVpZ58tlB2NNZv5Z6YqwMyLeUbb9iVbrzszzRtbRoG1nAeszMyNiiFpyXpaZV7Z88QOm12IdEUdRuyHCrSPjGsS6mRuAd0fE4qjdse7dZZyKLsabiNi//F1M7cYH/zxJua0J6rV4d5LfZedpaXn8Fmo33Pl2q3YPinZjHRGLqB20/Vxm/vfIzM1iOBm5HRHHAl+mtoPb8gCJXtVr8R5PbkfEyrp2vpdXDy753d1Ct+LdTDvxbpa3490vn9AboM5lD9yVqZOB2t0ak1rXzLvK8KvU+oqvo/YPZR2wpG6ZR6kdEdlF7WjJqjL+XGoXbt8DfANY2mSba4H7qF0PejEQZfzbyvp2A08BG5osvw9wJbVro+4AjijjPw78rO513AWsqfo97pWhl2Jdpp0P/GWLNjf9TAC/UT4Dm6l14a78Pe6locvx/ipwfxnOHmObneb2WPH+HrAdeL7Mc3rV73EvDb0U7zJtwvlN7X/8yPZvw//jHcWaWpfK3bz2u3H/VjEcT6zbyO0bgW1127+2bpq5PU3iXaaNJ7f/ltrNee4CbgKOqZvmd/fUxfuiklN7y9/z24n3WHk7avmG++Vlmvk9xcNI8CRJkiRJqsy079YrSZIkSZr+LE4lSZIkSZWzOJUkSZIkVc7iVJIkSZJUOYtTSZIkSVLlLE4lSZpkEXF+RPzxGNPPiIhVU9kmSZJ6jcWpJEnVOwOwOJUkDTR/51SSpEkQEecBnwAeo/Yj7j8EdgDnAEPUfvD914A1wHVl2g7gzLKKLwL7Ac8Bv5WZG6ey/ZIkTTWLU0mSuiwi3gpcChwPzAJ+BHwJ+NfMfKrM8+fAtsz8+4i4FLguM68q09YB52bmpog4HviLzDx56l+JJElTZ1bVDZAkqQ/9InB1Zj4HEBHXlvFvLkXpImA+cMPoBSNiPvAu4MqIGBk9Z9JbLElSxSxOJUmaHI26Jl0KnJGZd0fEp4BfbjDPDOCZzFwzeU2TJKn3eEMkSZK672bggxHxhohYALyvjF8APBERs4GP1c2/s0wjM58FHomIDwNEzeqpa7okSdXwmlNJkiZB3Q2RfgxsAe4HdgN/UsbdCyzIzE9FxC8A/wS8CJwF7AX+ETgQmA1cnplfmPIXIUnSFLI4lSRJkiRVzm69kiRJkqTKWZxKkiRJkipncSpJkiRJqpzFqSRJkiSpchankiRJkqTKWZxKkiRJkipncSpJkiRJqpzFqSRJkiSpcv8PxXMcJTllrpsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,10))\n",
    "plt.grid=True\n",
    "df['profit'].plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,10))\n",
    "test_plot =sns.lineplot(x='date',y='profit',data=df1)\n",
    "test_plot.set_xticks(df1['date'][::20])\n",
    "test_plot.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1=df.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-09</td>\n",
       "      <td>1.948580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-16</td>\n",
       "      <td>0.685567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-23</td>\n",
       "      <td>1.654852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-30</td>\n",
       "      <td>2.334265</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date    profit\n",
       "0  2018-01-02  0.000000\n",
       "1  2018-01-09  1.948580\n",
       "2  2018-01-16  0.685567\n",
       "3  2018-01-23  1.654852\n",
       "4  2018-01-30  2.334265"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
